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Published: 26 February 2024

A Framework for the Interoperability of Cloud Platforms: Towards FAIR Data in SAFE Environments

Robert L. Grossman ORCID: orcid.org/0000-0003-3741-5739 1 ,
Rebecca R. Boyles 2 ,
Brandi N. Davis-Dusenbery 3 ,
Amanda Haddock 4 ,
Allison P. Heath 5 ,
Brian D. O’Connor 6 ,
Adam C. Resnick 5 ,
Deanne M. Taylor ORCID: orcid.org/0000-0002-3302-4610 5 , 7 &
Stan Ahalt ORCID: orcid.org/0000-0002-8395-1279 8

Scientific Data volume 11 , Article number: 241 ( 2024 ) Cite this article

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Computational platforms and environments

As the number of cloud platforms supporting scientific research grows, there is an increasing need to support interoperability between two or more cloud platforms. A well accepted core concept is to make data in cloud platforms Findable, Accessible, Interoperable and Reusable (FAIR). We introduce a companion concept that applies to cloud-based computing environments that we call a S ecure and A uthorized F AIR E nvironment (SAFE). SAFE environments require data and platform governance structures and are designed to support the interoperability of sensitive or controlled access data, such as biomedical data. A SAFE environment is a cloud platform that has been approved through a defined data and platform governance process as authorized to hold data from another cloud platform and exposes appropriate APIs for the two platforms to interoperate.

As the number of cloud platforms supporting scientific research grows 1 , there is an increasing need to support cross-platform interoperability. By a cloud platform, we mean a software platform in a public or private cloud 2 for managing and analyzing data and other authorized functions. With interoperability between cloud platforms, data does not have to be replicated in multiple cloud platforms but can be managed by one cloud platform and analyzed by researchers in another cloud platform. A common use case is to use specialized tools in another cloud platform that are unavailable in the cloud platform hosting the data. Interoperability also enables cross-platform functionality, allowing researchers analyzing data in one cloud platform to obtain the necessary amount of data required to power a statistical analysis, to validate an analysis using data from another cloud platform, or to bring together multiple data types for an integrated analysis when the data is distributed across two or more cloud platforms. In this paper, we are especially concerned with frameworks that are designed to support the interoperability of sensitive or controlled access data, such as biomedical data or qualitative research data.

There have been several attempts to provide frameworks for the interoperating cloud platforms for biomedical data, including those by the GA4GH organization 3 and by the European Open Science Cloud (EOSC) Interoperability Task Force of the FAIR Working Group 4 . A key idea in these frameworks is to make data in cloud platforms findable, accessible, interoperable and reusable (FAIR) 5 .

The authors have developed several cloud platforms operated by different organizations and were part of a working group, one of whose goals was to increase the interoperability between these cloud platforms. The challenge is that even when a dataset is FAIR and in a cloud platform (referred to here as Cloud Platform A), in general the governance structure put in place by the organization sponsoring Cloud Platform A (called the Project Sponsor below) requires that sensitive data remain in the platform and only be accessed by users within the platform. Therefore, even if a user was authorized to analyze the data, there was no simple way for the user to analyze the data in any cloud platform (referred to here as Cloud Platform B), except for the single cloud platform operated by the organization (Cloud Platform A).

There are several reasons for this lack of interoperability between cloud platforms hosting sensitive data: First, as just mentioned, for many cloud platforms, it is against policy to remove data from the cloud platform; instead, data must be analyzed within the cloud platform.

Second, in some cases, to manage the security and compliance of the data, often there is only a single cloud platform that has the right to distribute controlled access data; other cloud platforms may contain a copy of the data, but by policy cannot distribute it.

Third, a typical clause in a data access agreement requires that if the user elects not to use Cloud Platform A, the user’s organization is responsible for assessing and attesting to the security and compliance of Cloud Platform B. This can be difficult and time consuming unless there is a pre-existing relationship.

Fourth, once a Sponsor has approved a single cloud platform as authorized to host data and to analyze the hosted data, there may be a perception of increased risk to the Sponsor in allowing other third party platforms to be used to host or to analyze the data. Because of this increased risk, there has been limited interoperability of cloud platforms for controlled access data.

The consensus from the working group was that interoperability of data and an acceleration of research outcomes could be achieved if standard interoperating principals and interfaces could describe which platforms had the right to distribute a dataset and which cloud platforms could be used to analyze data.

In this note, we introduce a companion concept to FAIR that applies to cloud-based computing environments that we call a S ecure and A uthorized F AIR E nvironment (SAFE). The goal of the SAFE framework is to address the four issues described above that today limit the interoperability between cloud platforms. The cloud-based framework consisting of FAIR data in SAFE environments is intended to apply to research data that has restrictions on its access or its distribution or both its access and distribution. Some examples are: biomedical data 3 , 6 , including EHR data, clinical/phenotype data, genomics data, imaging data; social science data 7 and administrative data 8 . We emphasize that the environment itself is not FAIR in the sense of 5 , but rather that a SAFE environment contains FAIR data and is designed to be part of a framework to support the interoperability of FAIR data between two or more data platforms.

Also, SAFE cloud platforms are designed to support platform governance decisions about whether data in one cloud platform may be linked or transferred to another cloud platform, either for direct use by researchers or to redistribution. As we will argue below, SAFE is designed to support decisions between two or more cloud platforms to interoperate in the sense that data may be moved between them, but is not designed nor intended to be a security or compliance level describing a single cloud platform.

The proposed SAFE framework provides a way for a Sponsor to “extend its boundary” to selected third party platforms that can be used to analyze the data by authorized users. In this way, researchers can use the platform and tools that they are most comfortable with.

In order to discuss the complexities of an interoperability framework across cloud based resources, in the next section, we first define some important concepts from data and platform governance.

Distinguishing Data and Platform Governance

We assume that data is generated by research projects and that there is an organization that is responsible for the project. We call this organization the Project Sponsor . This can be any type of organization, including a government agency, an academic research center, a not-for-profit organization, or a commercial organization.

In the framework that we are proposing here, the Project Sponsor sets up and operates frameworks for (1) data governance and (2) platform governance. The Project Sponsor is ultimately responsible for the security and compliance of the data and of the cloud platform. Data governance includes: approving datasets to be distributed by cloud platforms, authorizing users to access data, and related activities. Platform governance includes: approving cloud platforms as having the right to distribute datasets to other platforms and to users and approving cloud platforms as authorized environments so that the cloud platforms can be used by users to access, analyze, and explore datasets.

By controlled access data , we mean data that is considered sensitive enough that agreements for the acceptable use of the data must be signed. One between the organization providing the data (the Data Contributor ) and the Project Sponsor and another between researchers (which we call Users in the framework) accessing the data and the Project Sponsor. Controlled access data arises, for example, when research participants contribute data for research purposes through a consent process, and a researcher signs an agreement to follow all the terms and conditions required by the consent agreements of the research participants or by an Institutional Review Board (IRB) that approves an exemption so that consents are not required.

Commonly used terms that are needed to describe SAFE are contained in Table 1 . Table 2 describes the roles and responsibilities of the Project Sponsor, Platform Operator, and User.

As is usual, we use the term authorized user , as someone who has applied for and been approved for access to controlled-access data. See Table 1 for a summary of definitions used in this paper.

One of the distinguishing features of our interoperability framework is that we formalize the concept of an authorized environment. An authorized environment is a cloud platform workspace or computing / analysis environment that is approved for the use or analysis of controlled access data.

Using the concepts of authorized user and authorized environment, we provide a framework enabling the interoperability between two or more cloud platforms.

SAFE Environments

Below we describe some suggested processes for authorizing environments, including having their security and compliance reviewed by the appropriate official or committee determined by the platform governance process. We also argue that the environments should have APIs so that they are findable, accessible and interoperable, enabling other cloud platforms to interoperate with it. As mentioned above, we use the acronym SAFE for S ecure and A uthorized F AIR E nvironments to describe these types of environments. In other words, a SAFE environment is a cloud platform that has been approved through a platform governance process as an authorized environment and exposes an API enabling other cloud platforms to interact with it (Fig. 1 ).

An overview of supporting FAIR data in SAFE environments.

In this paper, we make the case that SAFE environments are a natural complement to FAIR data and establishing a trust relationship between a cloud platform with FAIR data and a cloud platform that is a SAFE environment for analyzing data is a good basis for interoperability . Examples of the functionality to be exposed by the API and proposed identifiers are discussed below. Importantly, our focus is to provide a framework for attestation and approvals to support interoperability. Definition of the exact requirements for approvals is based on the needs of a particular project sponsor and out of scope of this manuscript.

Of course, a cloud platform can include both FAIR data and a SAFE environment for analyzing data. The issue of interoperability between cloud platforms arises when a researcher using a cloud platform that is a SAFE environment for analyzing data needs to access data from another cloud platform that contains data of interest.

We emphasize that the framework applies to all types of controlled-access data, (e.g., clinical, genomic, imaging, environmental, etc.) and that decisions about authorized users and authorized platforms depend upon the sensitivity of the data, with more conditions for data access and uses as the sensitivity of the data increases.

The SAFE framework that we are implementing uses the following identifiers:

SAFE assumes that cloud platforms have a globally unique identifier (GUID) identifying them, which we call an authorized platform identifier (APID) .

SAFE assumes that cloud platforms form networks consisting of 2 or more cloud platforms, which we call authorized platform network (APN) . Authorized platform networks have a globally unique identifier, which we call an authorized platform network identifier (APNI) . As an example, cloud platforms in an authorized platform network can sign a common set of agreements or otherwise agree to interoperate. A particular cloud platform can interoperate with all or selected cloud platforms in an authorized platform network.

SAFE assumes that geographic regions are identified by a globally unique identifier, which we call an Authorized Region ID (ARID). For example, the entire world may be an authorized region, or a single country may be the only authorized region. SAFE assumes that datasets that limit their distribution and analysis to specified regions identify these regions in their metadata.

To implement SAFE, we propose that a cloud environment support an API that exposes metadata with the following information:

Authorized Platform Identifier (APID)

A list of the Authorized Platform Network Identifiers (APNIs) that it belongs to.

A particular authorized platform network must also agree to a protocol for securely exchanging the APID and list of APNIs that it belongs to, such as transport layer security (TLS) protocol.

In addition, cloud platforms that host data that can be accessed and analyzed in other cloud platforms, should associated with each dataset metadata that specifies: a) whether the data can be removed from the platform (i.e. does the platform have the right to distribute data); b) a list of authorize platform networks that have been approved as authorized environments to access and analyze the data; and, c) an optional list of authorized region IDs (ARIDs) describing any regional restrictions on where the data may be accessed and analyzed.

Platform Governance

Examples of platform governance frameworks.

An example of a process for authorization of an environment is provided by the process used by the NIH Data Access Committees (DACs) through the dbGaP system 9 for sharing genomics data 10 . Currently, if a NIH DAC approves a user’s access to data, and if the user specifies in the data access request (DAR) application that a cloud platform will be used for analysis, then the user’s designated IT Director takes the responsibility for a cloud platform as an authorized environment for the user’s analysis of controlled access data, and a designated official at the user’s institution (the Signing Official) takes the overarching responsibility on behalf of the researcher’s institution.

As another example, the platform governance process may follow the “NIST 800-53 Security and Privacy Controls for Information Systems and Organizations” framework developed by the US National Institute for Standards and Technology (NIST) 11 . This framework has policies, procedures, and controls at three Levels - Low, Moderate and High, and each organization designates a person that can approve an environment by issuing what is called an Authority to Operate (ATO). More specifically, in this example, the platform governance process may require the following to approve a cloud platform as an authorized environment for hosting controlled access data: (1) a potential cloud platform implement the policies, procedures and controls specified by NIST SP 800-53 at the Moderate level; (2) a potential cloud platform have an independent assessment by a third party to ensure that the policies, controls and procedures are appropriately implemented and documented; (3) an appropriate official or committee evaluate the assessment, and if acceptable, approves the environment as an authorized environment by issuing an Authority to Operate (ATO) or following another agreed to process; (4) yearly penetration tests by an independent third party, which are reviewed by the appropriate committee or official.

Many US government agencies follow NIST SP 800-53, and a designated government official issues an Authority to Operate (ATO) when appropriate after the evaluation of a system 11 . In the example above, we are using the term “authority to operate” to refer to a more general process in which any organization decides to evaluate a cloud platform using any security and compliance framework and has completed all the steps necessary so that the cloud platform can be used. In the example, an organization, which may or may not be a government organization, uses the NIST SP 800-53 security and compliance framework and designates an individual within the organization with the role and responsibility to check that (1), (2) and (4) have been accomplished and issues an ATO when this is the case.

The right to distribute controlled access data

In general, when a user or a cloud platform is granted access to controlled access data, the user or platform does not have the right to redistribute the data to other users, even if the other user has signed the appropriate Data Access Agreements. Instead, to ensure there is the necessary security and compliance in place, any user accessing data as an authorized user must access the data from a platform approved for this purpose. We refer to platforms with the ability to share controlled access data in this way as having the right to distribute the authorized data.

One of the core ideas of SAFE is that data which has been approved for hosting in a cloud platform can be accessed and transferred to another cloud platform in the case that: the first cloud platform has the right to distribute the data and the second cloud platform is recognized as an authorized environment for the data following an approved process, such as described in the next section. There remains the possibility that the cloud platform requesting access to the data is in fact an imposter and not the authorized environment it appears to be. For this reason, as part of SAFE, we recommend that the cloud platform with the right to distribute data should verify through a chain of trust that it is indeed the intended authorized environment.

Basis for approving authorized environments

The guiding principle of SAFE is that research outcomes are accelerated by supporting interoperability of data across authorized environments. While the specific requirements may vary by project and project sponsor, in order to align with this principle, it is critical that Project Sponsors define requirements transparently and support interoperability when the requirements are met.

Above we provided examples of approaches and requirements project sponsors may use in approving an Authorized Environment. As mentioned above, NIST SP 800-53 provides a basis for authorizing an environment, but there are many frameworks for evaluating the security and compliance of a system that may be used. As an example, the organization evaluating the cloud platform may choose to use a framework such as NIST SP 800-171 12 , or may choose another process for approving a cloud platform as an authorized environment rather than issuing an ATO.

For example, both the Genomic Data Commons 6 and the AnVIL system 13 follow NIST SP 800-53 at the Moderate Level and the four steps described above. The authorizing official for the Genomic Data Commons is a government official at the US National Cancer Institute, while the authorizing official for AnVIL is an organizational official associated with the Platform Operator.

Two or more cloud platforms can interoperate when both the Sponsors and Operators each agree to: (1) use the same framework and process for evaluating cloud platforms as authorized environments; (2) each authorize one or more cloud platforms as authorized environments for particular datasets; (3) each agree to a common protocol or process for determining when a given cloud platform is following (1) and (2). Sometimes, this situation is described as the platforms having a trust relationship between them.

Basis for approving the right to distribute datasets

For each dataset, a data governance responsibility is to determine the right of a cloud based data repository to distribute data to an authorized user in an authorized environment. To reduce risk of privacy and confidentiality breach, the data governance process may choose to limit the number of data repositories that can distribute a particular controlled access dataset and to impose additional security and compliance requirements on those cloud based data repositories that have the right to distribute particular sensitive controlled-access datasets. These risks of course must be balanced with the imperative to accelerate research and improve patient outcomes which underlies the motivations of many study participants.

Interoperability

SAFE is focused on the specific aspect of interoperability of whether data hosted in one cloud platform can be analyzed in another cloud platform.

With the concepts of an authorized user, an authorized environment, and the right to distribute, interoperability is achieved when two or more cloud platforms have the right to distribute data to an authorized user in a cloud based authorized environment.

This suggests a general principle for interoperability: the data governance process for a dataset should authorize users, the platform governance process for a dataset should authorize cloud platform environments, and two or more cloud platforms can interoperate by trusting these authorizations .

Figure 2 summarizes some of the key decisions enabling two cloud platforms to interoperate using the SAFE framework.

Some of the key decisions for interoperating two cloud platforms using the SAFE framework.

Towards Fair Data in SAFE Environments

Today there are a growing number of cloud platforms that hold biomedical data of interest to the research community, a growing number of cloud-based analysis tools for analyzing biomedical data, and a growing challenge for researchers to access the data they need, since often the analysis of data takes place in a different cloud platform than the cloud platform that hosts the data of interest.

We have presented the concept of cloud-based authorized environments that are called SAFE environments, which are secure and authorized environments that are appropriate for the analysis of sensitive biomedical data. The role of platform governance is to identify the properties required for a cloud platform to be an authorized environment for a particular dataset and to approve a cloud based platform that holds controlled access data to distribute the data to specific authorized platforms.

By standardizing the properties to be a SAFE environment and agreeing to the principle that the data governance process for a dataset should authorize users and the platform governance process should authorize cloud platform environments, then all that is required for two or more cloud platforms to interoperate is for the cloud platforms to trust these authorizations. We can shorten this principle to: “authorize the users, authorize the cloud platforms, and trust the authorizations.” This is the core basis for interoperability in the SAFE framework. See Table 3 for a summary.

This principle came out of the NIH NCPI Community and Governance Working Group and is the basis for the interoperability of the data platforms in this group. We are currently implementing APID, APNI and AIRD identifiers as described above, as well as the dataset metadata describing whether a dataset can be redistributed or transferred to other data platforms for analysis.

Navale, V. & Bourne, P. E. Cloud computing applications for biomedical science: A perspective. PLOS Comput. Biol. 14 (no. 6), e1006144, https://doi.org/10.1371/journal.pcbi.1006144 (2018). Jun.

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Acknowledgements

This document captures discussions of the NIH Cloud-Based Platform Interoperability (NCPI) Community/Governance Working Group that have occurred over the past 24 months, and we want to acknowledge the contributions of this working group. This working group included personnel from federal agencies, health systems, industry, universities, and patient advocacy groups. However, this document does not represent any official decisions or endorsement of potential policy changes and is not an official work product of the NCPI Working Group. Rather, it is a summary of some of the working group discussions and is an opinion of the authors. Research reported in this publication was supported in part by the following grants and contracts: the NIH Common Fund under Award Number U2CHL138346, which is administered by the National Heart, Lung, and Blood Institute of the National Institutes of Health; the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services under the Agreement No. OT3 HL142478-01 and OT3 HL147154-01S1; National Cancer Institute, National Institutes of Health, Department of Health and Human Services under Contract No. HHSN261201400008C; and ID/IQ Agreement No. 17X146 under Contract No. HHSN261201500003I. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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Optimizing Deep Learning Recommender Systems' Training On CPU Cluster Architectures

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Published: 20 April 2010

Cloud computing: state-of-the-art and research challenges

Qi Zhang 1 ,
Lu Cheng 1 &
Raouf Boutaba 1

Journal of Internet Services and Applications volume 1 , pages 7–18 ( 2010 ) Cite this article

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Cloud computing has recently emerged as a new paradigm for hosting and delivering services over the Internet. Cloud computing is attractive to business owners as it eliminates the requirement for users to plan ahead for provisioning, and allows enterprises to start from the small and increase resources only when there is a rise in service demand. However, despite the fact that cloud computing offers huge opportunities to the IT industry, the development of cloud computing technology is currently at its infancy, with many issues still to be addressed. In this paper, we present a survey of cloud computing, highlighting its key concepts, architectural principles, state-of-the-art implementation as well as research challenges. The aim of this paper is to provide a better understanding of the design challenges of cloud computing and identify important research directions in this increasingly important area.

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Zhang, Q., Cheng, L. & Boutaba, R. Cloud computing: state-of-the-art and research challenges. J Internet Serv Appl 1 , 7–18 (2010). https://doi.org/10.1007/s13174-010-0007-6

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Cloud computing
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Cloud Computing Tutorials

12 Latest Cloud Computing Research Topics

Free AWS Course for AWS Certified Cloud Practitioner (CLF-C01) Start Now!!

Cloud Computing is gaining so much popularity an demand in the market. It is getting implemented in many organizations very fast.

One of the major barriers for the cloud is real and perceived lack of security. There are many Cloud Computing Research Topics , which can be further taken to get the fruitful output.

In this tutorial, we are going to discuss 12 latest Cloud Computing Research Topics. These Cloud computing topics will help in your researches, projects and assignments.

So, let’s start the Cloud Computing Research Topics.

List of Cloud Computing Research Topics

These Cloud Computing researches topics, help you to can eliminate many issues and provide a better environment. We can assoicate these issues with:

Virtualizations infrastructure
Software platform
Identity management
Access control

There is some important research direction in Cloud Security in areas such as trusted computing, privacy-preserving models, and information-centric security. These are the following Trending Cloud Computing Research Topics .

Green Cloud Computing
Edge Computing
Cloud Cryptography
Load Balancing
Cloud Analytics
Cloud Scalability
Service Model
Cloud Computing Platforms
Mobile Cloud Computing
Cloud Deployment Model
Cloud Security

i. Green Cloud Computing

Green Cloud Computing is a broad topic, that makes virtualized data centres and servers to save energy. The IT services are utilizing so many resources and this leads to the shortage of resources.

Green Cloud Computing provides many solutions, which makes IT resources more energy efficient and reduces the operational cost. It can also take care of power management, virtualization , sustainability, and recycling the environment.

ii. Edge Computing

Although edge computing has several benefits, it is frequently combined with cloud computing to form a hybrid strategy. In this hybrid architecture, certain data processing and analytics take place at the edge, while more intense and extensive long-term data storage and analysis happen in the central cloud infrastructure. The edge-to-cloud continuum refers to this fusion of edge and cloud computing.

iii. Cloud Cryptography

Cloud cryptography is the practise of securing data and communications in cloud computing environments using cryptographic methods and protocols. Sensitive data is secured against unauthorised access and possible security breaches by encrypting it both in transit and at rest.

By allowing consumers to keep control of their data while entrusting it to cloud service providers, cloud cryptography protects the confidentiality, integrity, and authenticity of that data. Cloud cryptography improves the security posture of cloud-based apps and services, promoting trust and compliance with data privacy rules by using encryption methods and key management procedures.

iv. Load Balancing

Load Balancing is the distribution of the load over the servers so that the work can be easily done. Due to this, the workload demands can be distributed and managed. There are several advantages of load balancing and they are-

Fewer chances of the server crash.
Advanced security.
Improvement in overall performance.

The load balancing techniques are easy to implement and less expensive. Moreover, the problem of sudden outages is diminished.

v. Cloud Analytics

Cloud analytics can become an interesting topic for researchers, as it has evolved from the diffusion of data analytics and cloud computing technologies . The Cloud analytics is beneficial for small as well as large organizations.

It has been observed that there is tremendous growth in the cloud analytics market. Moreover, it can be delivered through various models such as

Community model

Analysis has a wide scope, as there are many segments to perform research. Some of the segments are business intelligence tools , enterprise information management, analytics solutions, governance, risk and compliance, enterprise performance management, and complex event processing

vi. Scalability

Scalability can reach much advancement if proper research is done on it. Many limits can be reached and tasks such as workload in infrastructure can be maintained. It also has the ability to expand the existing infrastructure.

There are two types of scalability:

The applications have rooms to scale up and down, which eliminates the lack of resources that hamper the performance.

vii. Cloud Computing Platforms

Cloud Computing platforms include different applications run by organizations. It is a very vast platform and we can do many types of research within it. We can do research in two ways: individually or in an existing platform, some are-

Amazon’s Elastic Compute Cloud
IBM Computing
Microsoft’s Azure
Google’s AppEngine
Salesforce.com

viii. Cloud Service Model

There are 3 cloud service models. They are:

Platform as a Service (PaaS)
Software as a Service (SaaS)
Infrastructure as a Service (IaaS)

These are the vast topics for research and development as IaaS provides resources such as storage , virtual machines, and network to the users. The user further deploys and run software and applications. In software as a service , the software services are delivered to the customer.

The customer can provide various software services and can do research on it. PaaS also provides the services over the internet such as infrastructure and the customers can deploy over the existing infrastructure.

ix. Mobile Cloud Computing

In mobile cloud computing , the mobile is the console and storage and processing of the data takes outside of it. It is one of the leading Cloud Computing research topics.

The main advantage of Mobile Cloud Computing is that there is no costly hardware and it comes with extended battery life. The only disadvantage is that has low bandwidth and heterogeneity.

x. Big Data

Big data is the technology denotes the tremendous amount of data. This data is classified in 2 forms that are structured (organized data) and unstructured (unorganized).

Big data is characterized by three Vs which are:

Volume – It refers to the amount of data which handled by technologies such as Hadoop.
Variety – It refers to the present format of data.
Velocity – It means the speed of data (generation and transmission).

This can be used for research purpose and companies can use it to detect failures, costs, and issues. Big data along with Hadoop is one of the major topics for research.

xi. Cloud Deployment Model

Deployment model is one of the major Cloud Computing research topics, which includes models such as:

Public Cloud – It is under the control of the third party. It has a benefit of pay-as-you-go.

Private Cloud – It is under a single organization and so it has few restrictions. We can use it for only single or a particular group of the organization.

Hybrid Cloud – The hybrid cloud comprises of two or more different models. Its architecture is complex to deploy.

Community Cloud

x. Cloud Security

Cloud Security is one of the most significant shifts in information technology. Its development brings revolution to the current business model. There is an open Gate when cloud computing as cloud security is becoming a new hot topic.

To build a strong secure cloud storage model and Tekken issues faced by the cloud one can postulate that cloud groups can find the issues, create a context-specific access model which limits data and preserve privacy.

In security research, there are three specific areas such as trusted computing, information-centric security, and privacy-preserving models.

Cloud Security protects the data from leakage, theft, disaster, and deletion. With the help of tokenization, VPNs, and firewalls, we can secure our data. Cloud Security is a vast topic and we can use it for more researches.

The number of organizations using cloud services is increasing. There are some security measures, which will help to implement the cloud security-

Accessibility
Confidentiality

So, this was all about Cloud Computing Research Topics. Hope you liked our explanation.

Hence, we can use Cloud Computing for remote processing of the application, outsourcing, and data giving quick momentum. The above Cloud Computing research topics can help a lot to provide various benefits to the customer and to make the cloud better.

With these cloud computing research, we can make this security more advanced. There are many high-level steps towards security assessment framework. This will provide many benefits in the future to cloud computing. Furthermore, if you have any query, feel free to ask in the comment section.

Did you like this article? If Yes, please give DataFlair 5 Stars on Google

Tags: big data Cloud Analytics Cloud Computing Platforms cloud computing research Cloud Computing Research Topics Cloud Computing Topics Cloud Cryptography Cloud Deployment Model Cloud Scalability Cloud Security Cloud Service Model Edge Computing Green Cloud Computing Load Balancing Mobile Cloud Computing Research Topics on Cloud Computing

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Dear, I wants to write a research paper on the cloud computing security, will also discuss the comparison of the present security shecks vs improvement suggested, I am thankful to you, as your paper helps me…

hay thanks for this valueable information dear i am just going to start my research in cloud computing from scratch i dnt now more about this field but i have to now work hard for this so plz give me idea how i start with effiecient manner

Hey Yaseen, Research is a great way to explore the entire topic. But it is recommended you master Cloud computing first, then start your research. Refer to our Free Cloud Computing Tutorial Series You can research on topics like Cloud Security, Optimization of resources, and Cloud cryptography.

Hi, Thank you for your article. I’m working on Cloud Computing Platforms research paper. Would you recommend any sources where I can get a real data or DB with numbers on cloud computing platforms. So, I can analyze it, create graphs, and draw a conclusion. Thank you

….or any sources with data on Cloud Service Models. Thank you

Can you please provide your contact details as I am also starting to research on Cloud Computing, Am a 11 years exp Consultant in an MNC working in Large Infrastructure. My email is partha.059@gmail .com so that we can communicate accordingly.

Can you please put some references you used, so that we can refer for more information? Thanks.

Hi, Very much pleased to know the latest topic for research. very informative, thanks for this i am interested in optimizing the resource here when i say resource it becomes too vast in terms of cloud computing components according to the definition of cloud computing. bit confused to hit the link.. could you plz.

hello iam searching for research gap in cloud computing I cant identify the problem please suggest me research topic on cloud computing

hello I am searching for research gap in cloud computing I cant identify the problem please suggest me research topic on cloud computing

we discuss optimization of resources, the gaps available

I want to do research in cloud databases,may i know the latest challenges in cloud databases?

I am a student of MS(computer science) and i am currently finding research topics in the area of cloud computing, Please let me know the topic of cloud computing and as well research gap so i will continue the research ahead with research gap.

Hi I am a student of MS(computer science) and i am currently finding research topics in the area of cloud computing, Please let me know the topic of cloud computing and as well research gap so I will continue the research.

What is Cloud Computing?

Cloud computing is the practice of storing and accessing data and applications on remote servers hosted over the internet, as opposed to local servers or the computer’s hard drive. Cloud computing, often known as Internet-based computing, is a technique in which the user receives a resource as a service via the Internet. Files, photos, documents, and other storable documents can all be considered types of data that are stored.

Let us look at the latest in cloud computing research for 2024! We’ve compiled 15 important cloud computing research topics that are changing how cloud computing is used.

1. Big Data

Big data refers to the large amounts of data produced by various programs in a very short duration of time. It is quite cumbersome to store such huge and voluminous amounts of data in company-run data centers . Also, gaining insights from this data becomes a tedious task and takes a lot of time to run and provide results, therefore cloud is the best option. All the data can be pushed onto the cloud without the need for physical storage devices that are to be managed and secured. Also, some popular public clouds provide comprehensive big data platforms to turn data into actionable insights.

DevOps is an amalgamation of two terms, Development and Operations . It has led to Continuous Delivery , Integration, and Deployment therefore reducing boundaries between the development team and the operations team . Heavy applications and software need elaborate and complex tech stacks that demand extensive labor to develop and configure which can easily be eliminated by cloud computing . It offers a wide range of tools and technologies to build , test , and deploy applications within a few minutes and a single click. They can be customized as per the client’s requirements and can be discarded when not in use hence making the process seamless and cost-efficient for development teams .

3. Cloud Cryptography

Data in the cloud needs to be protected and secured from foreign attacks and breaches . To accomplish this, cryptography in the cloud is a widely used technique to secure data present in the cloud . It allows users and clients to easily and reliably access the shared cloud services since all the data is secured using either encryption techniques or by using the concept of the private key . It can make the plain text unreadable and limit the view of the data being transferred. Best cloud cryptographic security techniques are the ones that do not compromise the speed of data transfer and provide security without delaying the exchange of sensitive data.

4. Cloud Load Balancing

It refers to splitting and distributing the incoming load to the server from various sources. It permits companies and organizations to govern and supervise workload demands or application demands by redistributing, reallocating, and administering resources between different computers, networks, or servers. Cloud load balancing encompasses holding the circulation of traffic and demands that exist over the Internet. This reduces the problem of sudden outages, results in an improvement in overall performance, has rare chances of server crashes and also provides an advanced level of security. Cloud-based server farms can accomplish more precise scalability and accessibility using the server load balancing mechanism . Due to this, the workload demands can be easily distributed and controlled.

5. Mobile Cloud Computing

It is a mixture of cloud computing , mobile computing , and wireless network to provide services such as seamless and abundant computational resources to mobile users, network operators, and cloud computing professionals. The handheld device is the console and all the processing and data storage takes place outside the physical mobile device. Some advantages of using mobile cloud computing are that there is no need for costly hardware, battery life is longer, extended data storage capacity and processing power, improved synchronization of data, and high availability due to “store in one place, accessible from anywhere”. The integration and security aspects are taken care of by the backend that enables support to an abundance of access methods.

6. Green Cloud Computing

The major challenge in the cloud is the utilization of energy-efficient and hence develop economically friendly cloud computing solutions. Data centers that include servers , cables , air conditioners , networks , etc. in large numbers consume a lot of power and release enormous quantities of Carbon Dioxide in the atmosphere. Green Cloud Computing focuses on making virtual data centers and servers to be more environmentally friendly and energy-efficient. Cloud resources often consume so much power and energy leading to a shortage of energy and affecting the global climate. Green cloud computing provides solutions to make such resources more energy efficient and to reduce operational costs. This pivots on power management , virtualization of servers and data centers, recycling vast e-waste , and environmental sustainability .

7. Edge Computing

It is the advancement and a much more efficient form of Cloud computing with the idea that the data is processed nearer to the source. Edge Computing states that all of the computation will be carried out at the edge of the network itself rather than on a centrally managed platform or data warehouse. Edge computing distributes various data processing techniques and mechanisms across different positions. This makes the data deliverable to the nearest node and the processing at the edge . This also increases the security of the data since it is closer to the source and eliminates late response time and latency without affecting productivity

8. Containerization

Containerization in cloud computing is a procedure to obtain operating system virtualization . The user can work with a program and its dependencies utilizing remote resource procedures . The container in cloud computing is used to construct blocks, which aid in producing operational effectiveness , version control , developer productivity , and environmental stability . The infrastructure is upgraded since it provides additional control over the granular activities of the resources. The usage of containers in online services assists storage with cloud computing data security, elasticity, and availability. Containers provide certain advantages such as a steady runtime environment , the ability to run virtually anywhere, and the low overhead compared to virtual machines .

9. Cloud Deployment Model

There are four main cloud deployment models namely public cloud , private cloud , hybrid cloud , and community cloud . Each deployment model is defined as per the location of the infrastructure. The public cloud allows systems and services to be easily accessible to the general public . The public cloud could also be less reliable since it is open to everyone e.g. Email. A private cloud allows systems and services to be accessible inside an organization with no access to outsiders. It offers better security due to its access restrictions. A hybrid cloud is a mixture of private and public clouds with critical activities being performed using the private cloud and non-critical activities being performed using the public cloud. Community cloud allows systems and services to be accessible by a group of organizations.

10. Cloud Security

Since the number of companies and organizations using cloud computing is increasing at a rapid rate, the security of the cloud is a major concern. Cloud computing security detects and addresses every physical and logical security issue that comes across all the varied service models of code, platform, and infrastructure. It collectively addresses these services, however, these services are delivered in units, that is, the public, private, or hybrid delivery model. Security in the cloud protects the data from any leakage or outflow, theft, calamity, and removal. With the help of tokenization, Virtual Private Networks , and firewalls , data can be secured.

11. Serverless Computing

Serverless computing is a way of running computer programs without having to manage the underlying infrastructure. Instead of worrying about servers, networking, and scaling, you can focus solely on writing code to solve your problem. In serverless computing, you write small pieces of code called functions. These functions are designed to do specific tasks, like processing data, handling user requests, or performing calculations. When something triggers your function, like a user making a request to your website or a timer reaching a certain time, the cloud provider automatically runs your function for you. You don’t have to worry about setting up servers or managing resources.

12. Cloud-Native Applications

Modern applications built for the cloud , also known as cloud-native applications , are made so to take full advantage of cloud computing environments . Instead of bulky programs like monolithic systems , they’re built to prioritize flexibility , easy scaling , reliability , and constant updates . This modular approach allows them to adapt to changing needs by growing or shrinking on demand, making them perfect for the ever-shifting world of cloud environments. Deployed in various cloud environments like public, private, or hybrid clouds, they’re optimized to make the most of cloud-native technologies and methodologies . Instead of one big chunk, they’re made up of lots of smaller pieces called microservices .

13. Multi-Cloud Management

Multi-cloud management means handling and controlling your stuff (like software, data, and services) when they’re spread out across different cloud companies, like Amazon, Google, or Microsoft. It’s like having a central command center for your cloud resources spread out across different cloud services. Multi-cloud gives you the freedom to use the strengths of different cloud providers. You can choose the best service for each specific workload, based on factors like cost, performance, or features. This flexibility allows you to easily scale your applications up or down as required by you. Managing a complex environment with resources spread across multiple cloud providers can be a challenge. Multi-cloud management tools simplify this process by providing a unified view and standardized management interface.

14. Blockchain in Cloud Computing

Cloud computing provides flexible storage and processing power that can grow or shrink as needed. Blockchain keeps data secure by spreading it across many computers. When we use them together, blockchain apps can use the cloud’s power for big tasks while keeping data safe and transparent. This combo boosts cloud data security and makes it easy to track data. It also lets people manage their identities without a central authority. However, there are challenges like making sure different blockchain and cloud systems work well together and can handle large amounts of data.

15. Cloud-Based Internet of Things (IoT)

Cloud-based Internet of Things (IoT) refers to the integration of cloud computing with IoT devices and systems. This integration allows IoT devices to leverage the computational power, storage, and analytics capabilities of cloud platforms to manage, process, and analyze the vast amounts of data they generate. The cloud serves as a central hub for connecting and managing multiple IoT devices, regardless of their geographical location. This connectivity is crucial for monitoring and controlling devices remotely.

Also Read Cloud computing Research challenges 7 Privacy Challenges in Cloud Computing Difference Between Cloud Computing and Fog Computing

Cloud computing has helped businesses grow by offering greater scalability , flexibility , and saving money by charging less money for the same job. As cloud computing is having a great growth period right now, it has created lots of employment opportunities and research work is done is different areas which is changing the future of this technology. We have discussed about the top 15 cloud computing research topics . You can try to explore and research in these areas to contribute to the growth of cloud computing technology .

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15+ Cloud Computing Projects With Source Code

Introduction, importance of cloud computing projects, cloud computing projects ideas, cloud computing projects for beginners, 1. attendance system, 2. bus ticketing and payment system, 3. host a dynamic website, 4. host a static website using aws or other clouds, 5. website without a server, intermediate cloud computing projects with source code, 6. system for online blood banking that is hosted in the cloud, 7. cloud-based conversational interface, 8. bookstore on the cloud, 9. smart traffic management system that is cloud-based, 10. cloud-based e-learning, advanced cloud computing projects with source code, 11. iot remote monitoring and control, 12. project for bug tracking in cloud computing, 13. file storage system using hybrid cryptography cloud computing project, 14. create a personal cloud, 15. repair techniques for transportable storage devices, 16. project to automate the university’s online services, 17. cloud computing for rural banking., 18. data leaks detection project, q1: how do i create a project in cloud computing, q2: what are examples of cloud computing, q3: does cloud computing require coding, additional resources.

One of the most significant ways to acquire a skill is to apply it, and what better way to accomplish this than to work on projects? So in this article, we’re providing the best cloud computing projects that you can draw inspiration from to work on your own projects. We encourage finishing numerous projects to master the various capabilities and functionalities of Django. We have provided projects of various skill levels so you may select according to your competence. Let’s get started.

In this article, we have discussed Cloud Computing Projects with their source code. Read on to know further.

Cloud computing applications are becoming more widespread across various fields, technologies, sizes, and applications. In addition to providing you with adequate exposure and experience on cloud technologies, cloud computing-based mini projects or real-time cloud computing projects will also provide you with other skills, including data analytics, business intelligence, network management, and analytical abilities, among others. It is feasible, for example, to work on cloud computing research projects or deploy cloud computing for large data projects, among other things. With the tremendous rise of both users of cloud computing technologies, there is a significant demand for projects including both technologies. Cloud computing offers a variety of applications that may be implemented using various computer languages and frameworks. One may create cloud computing projects in various computer languages, including Java, Android, PHP, and any other widely-used programming language available.

Confused about your next job?

You may use cloud computing projects for learners in various ways throughout their academic careers. For final-year engineering students, cloud computing projects for MTech students may be built utilizing cloud delivery and deployment methods and other cloud computing technologies. These cloud project ideas might be your go-to resource for inspiration and guidance when it comes to final-year projects. Programs based on cloud computing have applications in various industries and commercial areas, including entertainment, education, healthcare, retail, finance, and marketing, among others.

When it comes to cloud computing projects, both example projects and project names may be quite beneficial for students around the world alike. You may engage in these new projects to grow and enhance your knowledge and abilities in the subject of cloud computing, as well as other technologies if you so want.

Data security in cloud computing, for example, is a critical field, and working on data security cloud projects will allow you to acquire abilities in cloud computing, risk management, data security, and privacy, among other things.

We have a list of 15 types of cloud computing project ideas, along with the source code link.

Cloud computing is among the most well-known and most sought-after new technologies of our day. It offers end-users with computer system resources like computational power and data storage, among other things. Microsoft, Google, and Amazon Web Services (AWS) are all giants in their fields. Amazon was the first to introduce it, and they have been at the forefront of the industry since its debut. This article on “cloud computing projects” might assist if you are designing projects.

Cloud computing is based on three main Service models: PaaS (Platform as a Service), SaaS (Software as a Service), and IaaS (Infrastructure as a Service). In this section, we’ll take a deep dive into the techniques and high-demand Cloud computing projects that you may utilize to assist you in getting a decent job by generating a concept to create the greatest cloud computing projects available today.

The attendance system records an employee’s or student’s attendance and keeps the information in the cloud. When it scans the card, it enters information such as the in-time, the ID number, and the out-time. This will assist an administrator in removing or adding users and tracking the number of hours an employee or student has spent on the premises.

Source Code Link

Passengers will be able to purchase a bus pass on the internet as part of this trial. Bus booking, scheduling, and payment options are all available via the site, and passengers may purchase a bus pass by logging into the portal with their login credentials.

When a web page is dynamic, users can engage in interactive user interactions. You will greatly aid the aims of businesses by using a dynamic website. In this project, you will host a dynamic website on Amazon Web Services (AWS), and you will use client and server-side languages such as CSS, PHP, HTML, ASP, and JavaScript in the website building process to accomplish this.

In this cloud services project, you will make use of Amazon S3, a straightforward web-based cloud repository provided by Amazon to store static web pages. (documentation pages, blog pages, and so forth) When developing this project, you will use front-end technologies such as HTML and CSS to aid in the development process.

Using serverless cloud computing architecture will allow you to deploy products more quickly and efficiently. In addition, serverless websites provide several benefits, including scalability, the ability to charge users depending on their use of serverless environments such as DynamoDB, API, S3, and consumption.

In this assignment, you will design a blood bank system that includes blood type, donor information, storage space, and blood deposit locations. The information about the blood bank is saved on the cloud. The technology will assist users in identifying blood donors by comparing the information recorded in the database with the information entered into the system.

A chatbot is a piece of artificial intelligence software. Most businesses have used chatbots on their websites to improve customer support while also increasing efficiency. You will develop the chatbot in this project in Python, and it will speak with users, answer their questions, and gather the information you will save in a cloud database.

For this project, you will first create a book shop management system that will organize books into discrete categories and sections that will be easily accessible to end-users. The user searches for a certain book by entering the author’s name or the book’s title. The information and data are saved in a cloud-based environment.

Depending on their movement, this initiative will reduce the amount of time that motor vehicles are stuck in traffic during peak hours. A wireless communication system and sensors will be installed to increase efficiency. It also uses data extraction methods to get information that you may utilize in decision-making.

E-learning is a method of learning that allows a person to study from anywhere in the world. You will store the instructional materials, books, videos, and control information for this project on the project’s website, which will be organized by category. The information from the website is then kept in the cloud.

The Internet of Things links various devices to the internet, and the data collected is stored in the cloud until you can evaluate it.

Utilizing Arduino and electric eyes (sensors), you will gather data for this project, which you will then send to a Raspberry using a serial connection. The information gathered is stored in the cloud and can only be accessed by utilizing the MySQL database, which is not included.

This project will allow an administrator to investigate a problem and then interact with a customer using an application created specifically for this purpose. To make it simpler to identify new defects and solve them in a short amount of time, the system will automatically produce tags and labels for them.

This project is developing a cloud-based file storage system that uses hybrid cryptography. You will develop a system to safeguard documents stored in a database by encrypting them for use in this project. Blowfish is employed in encrypting data with a high output while using the least amount of time. When the papers are hosted on a distant server, they are encrypted using three different encryption techniques to provide greater security.

The Raspberry Pi board will be used to develop this project, which will result in a private cloud. To complete the created method, you will want a hard drive, a micro SD card, and a Raspberry Pi. After you’ve connected the components, you’ll be able to access your files from any location.

This project will repair and recreate information/data bits that have been lost due to failures of the repository nodes. The data is to be kept in the cloud so that you may retrieve it more quickly in the event of a disaster. After that, you will examine the rectification techniques and demonstrate productivity improvements.

During this project, your system will gather information about staff members, professors, student data, and visitor data from various sources. The information is gathered and structured so that you may reuse it later. In the next step, the information obtained is saved in the cloud.

This cloud computing project is intended to assist in hosting a banking system over the internet, allowing users to access their accounts without having to visit a financial institution physically. This will contribute to the improvement of economic activity.

This cloud computing initiative will aid in the prevention and management of data breaches as a result of SQL injection attacks. It will encrypt data and then store it in AESX encryption form, safeguarding it against Injection leakage and other threats. When you pay with a credit card, our initiative will guarantee that your information is secure.

Using cloud computing projects has a tremendous potential to modify the technical environment to improve the present company circumstances. As a result, if we can expand and improve technology, it will have a significant influence on enterprises and society as a whole. However, as the breadth of innovation continues to expand, the execution of such initiatives is a challenge that needs careful consideration and a willingness to take risks.

However, cloud technology is such a remarkable thing that the techies have already established various projects, and there are many more that are yet to be constructed in the current cutting edge technology and research and development, which continues to work for a better tomorrow for every one of us in the future. If you are familiar with the cloud computing area and technology, you may be able to participate in this cutting-edge technology. If this is the case, it is never too late to upgrade your skills. Learn cloud computing from some of the most knowledgeable people in the field, all with the help of a dedicated mentor.

Ans. The following are some cloud computing projects for beginners that you may construct to get more knowledge about the technology while also having fun:

Cloud Computing is being used to automate campus operations.
Injection Prevention and Detection of Data Leaks (SQL Injection Prevention).
Cloud-based student data chatbot with a human interface.
Bus Ticketing System that operates in the cloud.
Using the Cloud for Android Offloading.

Ans. Examples of Cloud Computing

Salesforce is a software-as-a-service (Saas) company.
DigitalOcean offers Infrastructure-as-a-Service (IaaS).
AWS offers Platform-as-a-Service (Saas).
Dropbox is a file-sharing and data-storage service.
Civic Analytics is a company that specializes in big data analysis.
Carbonite is the company in charge of data governance.
Forcepoint is a cyber-security firm.

Ans. Take cloud computing classes and begin utilizing a public or private cloud computing service to get a feel for the technology before investing your time and money in it. It is not necessary to be a programmer.

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Top 22 Cloud Computing Project Ideas in 2024 [Source Code]

Home Blog Cloud Computing Top 22 Cloud Computing Project Ideas in 2024 [Source Code]

The simplest and most effective way to gain proficiency in a domain is to focus on getting hands-on experience. When you work on live projects, you face real issues, gain familiarity with the actual scenarios, and gain expert-level understanding. So, when you plan and start your career in the cloud industry, you should work on a cloud computing project. It will help you understand the industry better. Moreover, you learn about the future scope of cloud computing. Based on this experience, you can choose the certifications that can boost your career and help you fetch excellent job opportunities. The idea behind working on cloud computing projects is to understand the field and plan the professional journey to get fruitful results.

In this article, we will discuss what is a cloud computing project, list of cloud computing project ideas based on skills, and a few examples for better understanding.

List of Cloud Computing Projects Ideas in 2024

Here is a list of curated cloud computing projects for all level skills, one should know in 2024:

Cloud-enabled attendance system
Online blood bank system
Online cloud-enabled bookstore system
Data redundancy removal system
Detecting data leaks using SQL injection
Cloud-based bus pass system
Making a chatbot
Secure text transfer
Bug tracking functionality


Attendance tracking	Online blood bank system	Bug tracking
Bus ticketing	Information Chatbot	File storage system using hybrid cryptography
Automation of university or college data	Online bookstore	Rural banking
Personal cloud	E-learning	Data leaks
Android Offloading

Top Cloud Computing Projects [Based on Levels]

Learning cloud computing starts with getting hands-on experience. Check out the and get started with the cloud:

1. Cloud-enabled attendance system

We can use a cloud-enabled automatic attendance system to scan details. Also, all the scanned information can be directly synchronized and stored on the cloud in real-time. Detailed information like check-in time, check-out time, date, and total working hours, to name a few, can be stored and saved. Administrators must register new students/employees on the system and provide some personal information.

Source Code: Cloud-Enabled Attendance System

Advantages Of a Cloud-Enabled Attendance System:

Data and Analytics: You can easily generate reports
Flexibility: You can track attendance in a variety of ways
Remote management: Cloud-based attendance systems make use of software that can be accessed from anywhere on any device that has Internet access.

Disadvantages Of a Cloud-Enabled Attendance System:

Not effective in monitoring buddy punching: This software is ineffective at detecting buddy punching. There is a greater possibility of malpractice occurring here. However, if it is equipped with biometric technology, it can be properly monitored.
Difficult to maintain and repair:nMaintaining and repairing software is difficult. Though it may be uncommon, once damaged, there will be costs associated with repairing it.
Ineffective when there is no power supply: Without a power supply, the software is of no use. The entire system is powered by electricity. This is not the case with the traditional method of taking attendance.

2. Online blood bank system

Using cloud computing, we can create a central repository for numerous blood deposits, including blood details and depositor information. The blood details would include blood type, storage area, and storage date to help maintain and monitor the blood depositors. This cloud-based system would allow for greater transparency in determining the availability of the desired blood depositor. This system will also contain patient and contact information.

Source Code : Online Blood Bank System

Advantages of Online Blood Bank System

Error probability is reduced to a minimum.
Easy and effective information retrieval.
The system shows the blood nearing expiry and those that have expired. Hence the unhealthy blood can easily be discarded.

3. Online cloud-enabled bookstore system

This system can function as an internet bookstore by utilizing SQL and C#. The books would be divided into sections to help users find their desired book without becoming overwhelmed by a database. Additionally, the bookstore records additional information such as a brief synopsis of the books. A notification system is added to help users stay up to date on their eagerly anticipated books and their availability.

Source Code: Online Cloud-Enabled Bookstore System

Advantages of Online Cloud-Enabled Book Store System

Lower costs as users are not required to purchase a powerful computer or server to support the system's operation.
Lower barriers to use. uses the service through the user's browser, the overall interface will be clearer and clearer, and the display effect of each functional module will be more intuitive and adapt to the user’s device
Higher security as maintenance of the server is the responsibility of the system supplier.

4. Data redundancy removal system

This project is focused on accurately removing unnecessary and redundant data in a short amount of time. It accomplishes this by classifying the test data as redundant or false positive. Also, the cloud-enabled system validates the newly-added data to keep the database free from duplicity. If the data is not found in the database, new data gets appended.

Source Code: Data redundancy removal system

Advantages of Data Redundancy Removal System

Alternative data backup method
Better data security
Faster data access and updates
Improved reliability

5. Detecting data leaks using SQL injection

This cloud-enabled data leak detection system operates over the Internet and does not require any particular system configuration. The system aims to enhance security and provide measures against SQL injection hacking. By storing users’ information in AES 256 encryption form, it meets all the security needs. It injects SQL through a capability code and establishes a connection between the cloud server and the application itself; this system doubles the security against it.

Source Code: Data Leakage Detection

Advantages of This Project

Get 100% database security and detect data leakers effortlessly.
Distributors can easily identify counterfeit agents leaking their confidential data and take strict action against them.

6. Cloud-based bus pass system

It is a cloud-based adaptation of purchasing tickets over the Internet. This solves many common problems, such as misplaced, stolen, or incorrectly priced tickets. In addition, if the load on a typical bus booking website is too high, the website chokes and stops working. However, an additional load can be handled by provisioning new servers in the computing.

Source Code: Cloud-based Bus Pass System

Advantages of Cloud-based Bus Pass System

Allows customers to check the availability of bus tickets before purchasing them
Secure. Passengers must first register with the system to verify their identity. After they have been verified, the system allows them to book passes for any route online.
Users can recharge using their credit/debit cards.

7. Making a chatbot

A chatbot is an AI-enabled software designed to interact with users when they visit a website. These bots are assigned to websites to streamline user interaction when they land on the website for the first time. The goal is to provide real-time and immediate responses to customer inquiries. To work on the chatbot application, you can use retrieval-based or generative-based models. If you want to use the chatbot on a commercial website, you should pre-define the input patterns.

Source Code: Chatbot

Advantages of Chatbots

Seamless live communication
Reduced people-to-people interactions
Makes customer service available 24/7

8. Secure text transfer

Encryption is essential to protect confidential data safe against unauthorized access or misuse. This encryption safeguards confidential information in a key-password combination. This combination employs Diffie-Hellman key exchange, which applies to private and public encryption concepts.

This project can be used to exchange text messages while maintaining maximum security and speed. This system can be modified and repurposed to work for image exchange. SQL databases to store all information for exchange strengthen the entire system.

Source Code: Secure Text Transfer

Advantages of Secure Text Transfer System

Content is encrypted to prevent access by hackers and unauthorized people.
.NET framework simplifies the development process.

9. Bug tracking functionality

Using cloud computing, developers could identify the type and origin of bugs by simply logging into the application. The project will be divided into three parts: customer, administrator, and staff.

By entering a username and password, the customer will create an account. They can log in to the bug tracking application with their credentials and send a bug report with screenshots of the bugs they encountered. Staff can log in using their respective accounts to view bugs and determine whether they need to be fixed. And administrators can contact the user directly about the bugs they sent and quickly resolve them. Depending on the load of the reports, this can vary significantly.

Source Code: Bug Tracking System

Advantages of Bug Tracking System

Deliver a high-quality product.
Better communication and connectivity.
Better customer service.

Enroll in KnowledgeHut training and courses to start your journey today. We provide study materials, cloud computing projects pdf, and the best resources to help you reach your cloud computing goals. Reach out to us to know our Cloud Computing course duration and fee in detail .

Cloud Computing Projects for Beginners

Are you new to the cloud and looking to explore your knowledge in cloud computing? There is no better way than trying some hands-on experience with a few basic projects. Here is a list of cloud computing projects for beginners that you must certainly give it a try.

1. Attendance tracking

This allows schools, colleges, institutions, and even offices to keep track of students' and employees' absences. Students and employees can mark their attendance by logging in, which is saved in the database and can later be checked by the institute's office.

Source Code: Attendance Tracking

2. Bus ticketing

Allow passengers to book bus tickets remotely. There will be no more hassles or concerns if the ticket is misplaced. Distributing tickets and passes to passengers can be done quickly and seamlessly. Also, passengers can use the bus ticketing app to check updates such as seat availability, schedules and timings, discounts, and much more.

Source Code: Bus Ticketing

3. Automation of university or college data

This project will assist you in creating a portal for a university or college. This portal allows them to register students, track their placements in various companies, and view their final results.

While it provides separate login portals for teachers and students, it also serves as a liaison between staff, students, and companies to deliver necessary information, collect feedback, declares results, etc.

Source Code: Automation of University

4. Personal cloud

You can create a personal cloud server with this project. Raspberry Pi and a Micro SD card will be required to build a private cloud. The hard drive will be the primary cloud storage in this project, and it will help you understand how a cloud server works.

Source Code: Personal Cloud

5. Android Offloading

Installing and offloading the processing requirements of an application is strenuous and time-consuming. The android offloading project aims to solve the problem by making it easy for applications to overload the compute parts explicitly. Using static analysis, this framework enhances an app's functionality. Users can choose a process and files to be encrypted and stored in the cloud. Visit AWS Cloud Practitioner Essentials Certification Training and learn AWS from scratch.

Source Code: Android Offloading

Intermediate Cloud Computing Projects with Source Code

Suppose you have a basic understanding of the cloud basics and you are comfortable working with computing, storage, and security. In that case, you must try a step forward than the entry-level projects. Here is the list of intermediate cloud computing projects from GitHub with source code. Let us check each in detail:

1. Online blood bank system

This cloud-based application serves as a central information database for the various blood deposits, including the donor's name and blood type information. The cloud can also store information such as blood type, storage data, blood type availability in a given area, etc. This facilitates quick access to blood in an emergency.

GitHub Source Code: Online Blood Bank System

2. Information Chatbot

Most companies have implemented chatbots on their websites to improve customer service and increase efficiency. In this project, you will create a chatbot in Python that will interact with users, answer their questions, and collect data that you will save in a cloud database.

GitHub Source Code: Information Chatbot

3. Online bookstore

This application can keep a catalog of books with the title, author, price, and even the ability to read them online. For the convenience of the customers, the books can be classified according to several criteria, such as author, genre, year of publication, and so on.

GitHub Source Code: Online Bookstore

4. E-learning

Online education platforms are nothing new to today's generation. These platforms have their advantages, resources, and time and cost flexibility and thus rank among the most popular learning mediums. Converting the project to a cloud project can drastically reduce costs. A learning space where study materials and relevant videos are kept for the learner's benefit. They are available for students to access and use as needed.

GitHub Source Code: E-learning

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Advanced Cloud Computing Project Ideas with Source Code

If you are a professional and have a sound understanding of cloud technologies, then you must opt for advanced cloud computing projects to elevate your skills to the next level. Here are a few hard-to-crack cloud computing projects with source code:

1. Bug tracking

Bug tracking is a project aimed at detecting and tracking the type and location of a bug on a website or app. Some common real-world applications designed using this concept include Backlog and Zoho bug tracker.

GitHub Source Code: Bug tracking

2. File storage system using hybrid cryptography

The project's goal is to secure the files using hybrid cryptography. Such applications are used in banking applications and systems to protect information and data sets.

You can encrypt the files with Blowfish because it is accurate and fast. Use symmetric algorithms for decryption. Even in remote servers, the hybrid technique can provide exceptional cloud security. With this project, you can add data security to your skill set, which is in high demand due to the increased frequency of security risks and attacks. Cryptography will be used to convert the data sets into unreadable forms.

GitHub Source Code: File storage system

3. Rural banking

This cloud project aims to create a cloud-based banking system for rural areas where banking facilities and amenities are inadequate to provide people with banking convenience.

GitHub Source Code: Rural banking

4. Data leaks

SQL injection refers to data leakage in the database as a common business problem. It is an excellent portal for anyone working or planning to work as an e-commerce platform. The primary aim of SQL injectors is to safeguard data and secure the privacy of the information from scammers. Developers employ standard encryption technology to create this SQL injection system

GitHub Source Code: Data leaks

Best Platforms to Work on Cloud Computing Project

Cloud offers different platforms on which you can run your projects. These platforms provide specific features based on which you can handle projects where you need to manage those particular aspects. Some of the cloud computing project platforms are:

Microsoft Azure: Azure provides a wide range of services, making it the most accessible platform in the cloud environment. Any organization with any requirements can opt for Microsoft Azure as it will cater to all of them. It would be fair to say that Microsoft Azure is a dependable option for enterprises.
Google Cloud: This platform provides new-age companies with a trustworthy, user-friendly, and protective cloud environment to the organizations. You get enough services in Google Cloud to cater to all the IaaS or PaaS requirements.
IBM Cloud: The three models that IBM Cloud primarily focuses on are IaaS (infrastructure as a service), SaaS (software as a service), and PaaS (platform as a service). It is a cost-effective platform where you can make an adjustment to reduce the overall expense.

Importance of Cloud Computing Projects

Whether you a professional getting started with cloud computing or an experienced folk with experience in the cloud, these projects will help you streamline your learning process in many ways. Check out the importance of cloud computing projects and why it is a must for you:

Cloud computing applications cover many domains, technologies, scales, and applications. Cloud computing mini projects or real-time cloud computing projects will provide adequate exposure and experience with cloud technologies.
With the massive expansion of both technologies, virtualization and cloud computing projects are in high demand. Cloud computing has several applications in terms of programming languages and frameworks. Java cloud computing projects, Android cloud computing projects, PHP cloud computing projects, and other popular programming languages can be developed.
Cloud computing projects for students have many applications in their academic careers. Cloud delivery and deployment models can be used to develop cloud computing projects for final-year engineering or cloud computing projects for MTech. Cloud computing projects are used in entertainment, education, healthcare, retail, banking, marketing, and other industrial and business domains.

Factors Affecting Cloud Computing

Cloud computing based on the pay-as-you-go model is affected by a number of factors. Let us discuss each in brief:

Cost: The developers must keep in mind that it must be cost-effective and allow the company to achieve cost-saving benefits. Most businesses choose Cloud Computing because it is less expensive.
Application in the future: Its potential applications should be designed so that they not only benefit the company in terms of current needs but are also adaptable enough to benefit the organization in the future as changes occur.
Mobility: It is essential to design a Cloud Computing project to be easily moved between private and public clouds to check and access resources or data.
Security: Security is the top priority when considering the entire aspect of data and resources. As a result, data security should be prioritized while a project is being developed.
Increased bandwidth: When working in the cloud, it is important to consider increased bandwidth. Increased bandwidth significantly reduces transfer times, especially when handling big chunks of data.

I hope, we have covered the top cloud computing projects along with source code. Cloud is a high-demand domain with an increasing number of opportunities. Companies are switching to cloud environments because of the accessibility and data safety features. So, it would be fruitful to consider planning a career in this domain. If you can gain proficiency and prove your worth in the market, you can enjoy a monetarily sound and secure professional career. Start by getting all the information about this industry and find projects that can give you the right kind of experience. You can also join Cloud Computing certification courses that can train you in the right tools and techniques to help you establish a promising professional career in the cloud. If you plan everything strategically, your dream job is not far-fetched.

Frequently Asked Questions (FAQs)

These are the projects one must do to know how the notions of cloud computing can be applied in the real world.

Here are some cloud computing projects for beginners that you can build to learn more about the technology while also having fun:

A human-interfaced cloud-based student data chatbot.

Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).

The father of cloud computing is American computer scientist J.C.R. Licklider.

The cost considerations in a cloud computing project include predicting the cost of cloud service. Furthermore, the cost of tools and the expense of individual resources also get included in cost consideration.

The security considerations in a cloud computing project include network security risks. Furthermore, the cloud relies on shared resources, so you should consider separation and segmentation.

The common challenges in implementing a cloud computing project include data security and privacy issues, multi-cloud environments, and high network dependencies.

Kingson Jebaraj

Kingson Jebaraj is a highly respected technology professional, recognized as both a Microsoft Most Valuable Professional (MVP) and an Alibaba Most Valuable Professional. With a wealth of experience in cloud computing, Kingson has collaborated with renowned companies like Microsoft, Reliance Telco, Novartis, Pacific Controls UAE, Alibaba Cloud, and G42 UAE. He specializes in architecting innovative solutions using emerging technologies, including cloud and edge computing, digital transformation, IoT, and programming languages like C, C++, Python, and NLP.

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Cloud Computing Project Topics With Abstracts and Base Papers 2024

Embark on a journey through innovative research as we unveil M.Tech projects pushing the boundaries of technology. From revolutionizing pavement crack image segmentation with deep learning to addressing healthcare challenges in Mobile Cloud Computing (MCC) through the Modular Encryption Standard (MES), our projects reflect cutting-edge solutions. Explore the future of Big Data (BD) operations with our Big Cloud framework. Each project represents a commitment to advancing knowledge and overcoming challenges in the dynamic field of computer engineering. Welcome to a showcase where technology meets groundbreaking research!

M.Tech Projects Topics List In Cloud Computing

	Base Paper	Abstract
1.Enhancing Security of Health Information Using Modular Encryption Standard in Mobile Cloud Computing.
2.Security by Design for Big Data Frameworks Over Cloud Computing.
3.Cloud Computing-Based Framework for Breast Cancer Diagnosis Using Extreme Learning Machine.
4.HEPGA: A new effective hybrid algorithm for scientific workflow scheduling in cloud computing environment.
5.Performance Analysis of Scheduling Algorithms for Virtual Machines and Tasks in Cloud Computing
6.Genetic Algorithm-Based Task Scheduling in Cloud Computing Using MapReduce Framework.
7.DCHG-TS: a deadline-constrained and cost-effective hybrid genetic algorithm for scientific workflow scheduling in cloud computing.
8.Applications of Virtual Machine Using Multi-Objective Optimization Scheduling Algorithm for Improving CPU Utilization and Energy Efficiency in Cloud Computing.
9.A novel hybrid antlion optimization algorithm for multi-objective task scheduling problems in cloud computing environments.
10.A multi-objective Monarch Butterfly Algorithm for virtual machine placement in cloud computing.

Himanshu Garg

Experienced Engineering Mentor and Educator | Empowering Students to Excel. With a passion for guiding and empowering engineering students, I am dedicated to supporting their academic journey and fostering their success. With a strong background in Process Control (instrumentation), I completed my Mtech in 2020. Passionate about helping students excel, aims to introduce new modules addressing mental stress problems and other crucial areas in Engineer's Planet. Connect with me to explore opportunities for collaboration and support in engineering education.

Artificial Intelligence Project Topics With Abstracts and Base Papers 2024

Machine learning project topics with abstracts and base papers 2024, you may also like, computer science | c | c++ projects free..., computer science php projects free downloads, computer science projects | machine learning | deep..., data architecture: the evolution of next generation, application of ai in cybersecurity: benefits, uses, and..., go beyond basic chatbot: explore advanced nlp techniques, major projects on cyber security final year, tensorflow based projects for final year, machine learning final year projects 2024 | ai, cse,..., intensity analysis (build your own model using nlp..., leave a reply cancel reply.

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Title: litmus: fair pricing for serverless computing.

Abstract: Serverless computing has emerged as a market-dominant paradigm in modern cloud computing, benefiting both cloud providers and tenants. While service providers can optimize their machine utilization, tenants only need to pay for the resources they use. To maximize resource utilization, these serverless systems co-run numerous short-lived functions, bearing frequent system condition shifts. When the system gets overcrowded, a tenant's function may suffer from disturbing slowdowns. Ironically, tenants also incur higher costs during these slowdowns, as commercial serverless platforms determine costs proportional to their execution times. This paper argues that cloud providers should compensate tenants for losses incurred when the server is over-provisioned. However, estimating tenants' losses is challenging without pre-profiled information about their functions. Prior studies have indicated that assessing tenant losses leads to heavy overheads. As a solution, this paper introduces a new pricing model that offers discounts based on the machine's state while presuming the tenant's loss under that state. To monitor the machine state accurately, Litmus pricing frequently conducts Litmus tests, an effective and lightweight solution for measuring system congestion. Our experiments show that Litmus pricing can accurately gauge the impact of system congestion and offer nearly ideal prices, with only a 0.2% price difference on average, in a heavily congested system.

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New Distributed Cloud- And Network Architecture for True 3D Holography

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First Online: 01 July 2024
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Ingo Friese 5

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1138))

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The current 6G NeXt research project [ 1 ] is exploring the feasibility of using true 3D holography as a case study, establishing criteria for both communication and computing infrastructure. In a future holographic communication service, clients are dispersed throughout the network and engage in collaborative interactions. Holographic communication demands significant processing power, necessitating the inevitability of a high-speed distributed backbone computing infrastructure that embodies the concept of split computing. Moreover, seamless integration between processing facilities and wireless networks is imperative to deliver an immersive user experience [ 2 ].

This presentation is going to delineate the realm of true 3D holographic communication and its prerequisites. It introduces concepts of distributing computing tasks in a new way across conventional computing infrastructure and outlines a suitable solution approach, presenting innovative technological strategies based on a proposed comprehensive communication and computing architecture. True holography, as an exceptionally demanding example of future XR applications, highlights the necessity and challenges for telecommunication providers in designing new networks in conjunction with cloud infrastructure. Future generations of networks will bring us closer to the true convergence of connectivity and computing [ 3 ].

6gnext project homepage. https://6gnext.de/

Future network requirements for extended reality applications. Ericcson, Technical report 4 (2023). https://www.ericsson.com/en/reports-and-papers/ericsson-technology-review/articles/future-network-requirements-for-xr-apps

The next hyperconnected experience for all. Samsung Research, Technical report (2022). https://cdn.codeground.org/nsr/downloads/researchareas/6G

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Friese, I. (2024). New Distributed Cloud- And Network Architecture for True 3D Holography. In: Köhler-Bußmeier, M., Renz, W., Sudeikat, J. (eds) Intelligent Distributed Computing XVI. IDC 2023. Studies in Computational Intelligence, vol 1138. Springer, Cham. https://doi.org/10.1007/978-3-031-60023-4_1

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Multicloud security

Multicloud security: architecture and ultimate guide.

Understand multicloud network security architecture for AWS, Azure, GCP, and OCI. Read more to learn the details.

What is multicloud security?

Multicloud security is a cloud security solution that allows comprehensive data protection across multiple cloud platforms, including both private clouds and public clouds like AWS, Azure, Google Cloud Platform (GCP), and Oracle Cloud Infrastructure (OCI). Organizations can use multicloud security to protect all cloud platforms and their varying functions.

Cisco Multicloud Defense

Simplify security and gain multidirectional protection across public or private clouds to block inbound attacks, lateral movement, and data exfiltration.

Why is multicloud security important?

Multicloud adoption is no longer a choice—it's an essential element in the fast-paced, modern organization where agility and flexibility impact business success. While multicloud environments offer tremendous benefits to organizations, they also create greater complexity that can lead to security gaps and inefficiencies, making it difficult for organizations to achieve the full benefit of cloud economics.

To harness the full benefit of cloud economics, organizations need a strategy for multicloud security. This article reviews multicloud security architecture, requirements, challenges, and best practices to help organizations optimize their multicloud strategy regardless of where they are in their journey.

Multicloud is ubiquitous, security is not

Multicloud adoption has accelerated in recent years. In the 2022 Hybrid Cloud Trends report commissioned by Cisco, 82% of IT leaders reported they have adopted hybrid cloud and 58% of organizations use between two and three infrastructure-as-a-service (IaaS) clouds 1 . Gartner reported that, by 2023, 40% of all enterprise workloads would be deployed in cloud infrastructure and platform services, up from 20% in 2020 2 . Undoubtedly, organizations have embraced all the benefits multicloud environments have to offer. While the majority have already invested significantly into more than one cloud to support digital transformation and other initiatives, many plan additional investments to further enable their digital business.

Multicloud success, however, remains elusive for many organizations. Among midsize organizations, for example, only 50% report that multicloud has helped achieve business goals, according to a 2021 survey by HashiCorp 3 .

In conversations with customers, many have called out cost management, governance, and visibility as common barriers to adoption and deployment of multicloud environments, but one factor that consistently lingers at the top is security. In a 2023 Valtix survey, 51% of IT leaders agreed or strongly agreed that their company doesn't want to expand to additional clouds because of the security complexities.

One driver behind the challenges is the expectation that you can simply extend your data center or on-premise-security framework into the cloud. However, to solve the security complexities associated with multicloud environments, your strategy needs to adapt to the dynamic environment with a cloud-first approach.

This article recommends a security model that can help you advance on your multicloud journey at the speed of the cloud—and your business.

Figure 1. Tools used for achieving security requirements across cloud service providers

Challenges of multicloud security

Multicloud environments add additional layers of risk to organizations. Risk can stem from a multitude of challenges, including:

Cloud threats

Just as there are threats to on-premises environments, there are threats that affect multicloud environments too. Considering the diversity of threats that can affect an organization's cloud environment, it's no surprise that 73% of organizations are very or extremely concerned about cloud security. Some of these threats include:

Zero-day exploits
Cryptomining
Malicious insiders
Ransomware and lateral movement of threats

Data loss and breaches

The risk of breaches and data loss command the most attention. In the 2023 IBM Cost of a Data Breach Report 4 , the average cost for a data breach across the boards was US$4.45 million. Additional datapoints included cloud environments, noting 82% of breaches involved data stored in the cloud and 39% of breaches spanned across multiple environments. Breaches spanning across multiple environments also incurred a higher-than-average cost of US$4.75 million, making data loss prevention and protection against lateral movement a necessary focal point in any multicloud strategy.

While navigating the cloud threat landscape, organizations must grapple with numerous multicloud security challenges, including:

The complexities—and the gray areas and vagaries—of the shared responsibility model
Risks that are unique to the cloud, such as reduced visibility and control
The inherent open model of the cloud, which requires additional considerations
The inconsistent architecture and infrastructure of the various cloud environments
Additional issues such as talent shortage and compliance

Many of these aspects require granular expertise—not only in cloud networking and security but also in each cloud provider's product offerings and services, architecture, automation, and security tools—compounding the challenges.

The shared responsibility model: Complex, vague, and rigid

The shared security responsibility model of the public cloud keeps security teams on their toes. Providers typically offer guidelines, but in practice, you can't rely on them completely—and the lines sometimes appear fuzzy. This became especially evident considering recent exploits we've seen within cloud-provider services, which required the end users to mitigate while waiting for a fix.

In a traditional service outsourcing model, your provider would work with your team to clearly define the boundaries. That's not the case in the cloud.

Things get even more challenging in the constant parade of updates and new services from providers. They introduce dozens of services, hundreds of new features every year, and numerous updates. Developers eagerly consume the services because they solve specific problems or add new capabilities. The rapid pace of change makes their job easier—and the security team's job harder.

This throws security teams into a perpetual cycle of catch-up, trying to figure out the implications of each change. Multiply this challenge by the number of clouds you've deployed, and the problem is quickly exacerbated.

Figure 2. Shared responsibility model

Other challenges

Unique cloud security risks .

Reduced visibility and control are common problems, with 53% of surveyed cybersecurity professionals identifying a lack of visibility and 46% calling out inadequate control as their top barrier to adoption3. Other risks include insecure APIs and lack of a centralized view across multicloud.

The talent gap

The cybersecurity industry has grappled with a talent shortage for years, with the latest data showing a gap of 3.1 million security workers globally in 20205. Provider-specific security requires deep expertise with each cloud's configurations, intensifying the talent issue.

Policy enforcement

The variations in controls in individual clouds and app architectures result in inconsistent policy enforcement across your environment, leading to gaps in protection and reduced security posture.

Building layered defenses in the cloud

Although your cloud architecture and security approach are different from on-premises, the tenet of multilayered security still applies. There's no one-size-fits-all solution that covers all the threat vectors and types of attacks. When building out your security layers, consider capabilities such as:

Visibility into all your assets (apps, APIs, workloads, etc.) across all your clouds, as well as into your security monitoring and whether it's working as expected
Cloud network security, such as firewall, data loss protection (DLP), segmentation, and intrusion detection/intrusion prevention systems (cloud IDS/IPS)
Protection against web threats through web application firewall (cloud WAF) and malicious IP blocking
Context-aware security across app lifecycle (dev, test, prod) and type of apps (general, sensitive, compliance)
Extending these security layers from the data center or bolting them on top of your architecture is ineffective and introduces new problems, such as orchestrating and automating the tools across multicloud.

In contrast, a solution that delivers both networking and security in a cloud-native way has many benefits, it:

Offers advantages such as agility, scalability, and elasticity
Works seamlessly with your cloud apps
Enables continuous discovery of new apps and infrastructure and automatic policy based on app context

Implement active defense

Cloud vulnerabilities are one of the biggest challenges for security teams. Consequently, these teams devote much of their time to patching. But managing vulnerabilities alone will not protect you against zero-day threats. By the time a vendor knows about a new threat and creates a patch, it may be too late.

Just like on-premises, the multicloud needs both proactive and reactive defenses. Active defense enables you to block attacks, restrict unauthorized access to assets, and defend against new and emerging threats. The goal should be to break the attack kill chain in multiple places and not rely on a single point of failure in your defenses. For example, to stop an attacker on a breached server, a malicious insider, or a ransomware attack, an effective last stop is to restrict all outbound traffic to known categories of sites, domains, and URLs.

Requirements for a multicloud security solution

Although multicloud security solutions have different functionalities based on their category, they share a set of common criteria, such as simplicity of deployment and management. When evaluating a vendor's multicloud security solution, consider the following aspects:

Continuous visibility

To detect malicious activities such as data exfiltration, you need to combine your cloud asset information and threat intelligence with complete visibility into all traffic flows, including inbound from and outbound to the internet, east-west, and to platform-as-a-service (PaaS) services.

Comprehensiveness

A solution with a thorough and robust feature set will reduce or eliminate the need for multiple point products and enable you to consolidate your cloud security. Look for critical capabilities such as dynamic policy enforcement, segmentation, network protection (cloud firewall), and web protection.

Active defense capabilities

If your security only allows you to react to threats rather than proactively stop them, your team will always remain at least one step behind the adversary. In the past, active defense required an agent-based solution. Now, organizations can achieve active defense with an agentless approach, reducing deployment and maintenance challenges.

Cloud scalability

Business requirements and environments continuously change, and security needs to be able to quickly scale in and out to adapt to those changes. The multicloud security solution should automatically scale security to meet demand, discover new assets as they are implemented in the production environment, and apply context-based policy—so your team doesn't have to constantly worry about operating the tool across multiple clouds, regions, and accounts. The multicloud security solution should automatically scale security to meet demand, discover new assets as they are implemented in the production environment, and apply context-based policy—all without manual intervention, so your team doesn't have to constantly worry about operating the tool across multiple clouds, regions, and accounts.

Ease and speed of deployment

Your cloud security solution shouldn't amplify the complexities of an already complex multicloud environment, yet many vendors' products are difficult and time-consuming to deploy across public cloud infrastructure. Look for a turnkey solution that simply achieves outcomes, is fast to implement, and works natively in your environment. This will eliminate the need for admins to manually adapt the environment—instead, the solution "learns" the environment through the APIs in that cloud.

Single policy framework

A centralized control plane across disparate clouds enables you to enforce security policies consistently from one controller, simplifying multicloud management and alleviating complexity. To achieve this, the security solution should provide an abstraction layer that decouples the control plane and data plane.

Figure 3. Cisco Multicloud Defense's comprehensive approach to multicloud network security

Adopt unified, simplified, multicloud network security with Cisco Multicloud Defense

Cisco Multicloud Defense solves the complexities of deploying and managing security in multicloud environments. Delivered as a service, it unifies security controls across AWS, Azure, GCP, and OCI through a single control plane, bringing simplicity to complex multicloud environments.

Cisco Multicloud Defense delivers:

Layered, proactive defense through advanced security controls (including firewall, WAF, DLP, and IDS/IPS)
Deployments in as little as 5 minutes without additional infrastructure
Continuous, dynamic, real-time visibility into all your cloud apps and infrastructure
A single, dynamic policy framework for consistent, automatic policy enforcement across the multicloud
A flexible, open platform that integrates threat intelligence feeds and third-party solutions such as security information and event management (SIEM) and security orchestration and automation response (SOAR)

Today's IT and DevOps teams move fast to support digital transformations and other initiatives that keep your business competitive. Cisco Multicloud Defense helps your teams to achieve the full benefit of cloud economics with the skilled resources you already have and without compromising on security.

Embrace the multicloud world with the control you need

Multicloud adoption is no longer a choice—it's an essential element in the fast-paced, modern business environment where agility impacts the success of your business. Without understanding the full spectrum of challenges and requirements of the multicloud, it would be difficult to account for the obstacles and risk you may face on your cloud journey. You can overcome the hurdles by shifting to a cloud-first mentality— implementing security solutions that minimize complexity and risk by design, helping your organization securely stay in control in an ever-changing multicloud world.

Do you have questions? Do you want to see Cisco Multicloud Defense in action? Take our product tour , request a demo , or try it for yourself with our free trial .

References

2022 Global Hybrid Cloud Trends Report. 451 Research and Cisco Systems, 2022
Gartner Hype Cycle™ for Workload and Network Security, 2022
HashiCorp State of Cloud Strategy Survey, 2021
IBM Cost of a Data Breach Report, 2023
ISC2 Cybersecurity Workforce Study, 2020

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Top 10 Cloud Computing Research Topics of 2024
Big data in cloud computing research papers are having huge visibility in the industry. The paper "Targeted Influence Maximization based on Cloud Computing over Big Data in Social Networks" proposes a targeted influence maximization algorithm to identify the most influential users in a social network. ... PMP is a registered mark of the Project ...
Cloud computing research: A review of research themes, frameworks
This paper presents a meta-analysis of cloud computing research in information systems with the aim of taking stock of literature and their associated research frameworks, research methodology, geographical distribution, level of analysis as well as trends of these studies over the period of 7 years. ... Cloud computing research started to gain ...
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The Journal of Cloud Computing: Advances, Systems and Applications (JoCCASA) will publish research articles on all aspects of Cloud Computing. Principally, articles will address topics that are core to Cloud Computing, focusing on the Cloud applications, the Cloud systems, and the advances that will lead to the Clouds of the future.
Articles
Cloud environment is a virtual, online, and distributed computing environment that provides users with large-scale services. And cloud monitoring plays an integral role in protecting infrastructures in the clo... Hongxia He, Xi Li, Peng Chen, Juan Chen, Ming Liu and Lei Wu. Journal of Cloud Computing 2024 13 :115.
Adoption of cloud computing as innovation in the organization
We also explore the cybersecurity elements associated with cloud computing, focusing on intrusion detection and prevention and understanding how that can be applied in the cloud. Finally, we investigate the future research directions for cloud computing and expand this paper into further articles with experiments and results.
Cloud Computing: A Systematic Literature Review and Future Agenda
review is thought to inspire enterprises and managers that would like to use cloud computing in. terms of the scope, solution methods, factors, dimensions, and the results achieved in a holistic ...
A Framework for the Interoperability of Cloud Platforms ...
As the number of cloud platforms supporting scientific research grows, there is an increasing need to support interoperability between two or more cloud platforms. A well accepted core concept is ...
Cloud Computing
This paper is concerned with developing a software tool, called IMPaCT, for the parallelized verification and controller synthesis of large-scale stochastic systems using interval Markov chains (IMCs) and interval Markov decision processes (IMDPs), respectively. 10. 07 Jan 2024. Paper. Code.
Cloud Computing Continuum Research Topics and Challenges. A Multi
This paper presents a multi-source based analysis for the identification of cloud computing research challenges as part of the road mapping methodology followed in the HUB4CLOUD project. The analysis consists of an in-depth study of several sources including analysis of the international context, analysis of academic venues, interviews with ...
Next generation cloud computing: New trends and research directions
Next generation cloud computing systems are aimed at becoming more ambient, pervasive and ubiquitous given the emerging trends of distributed, heterogeneous and ad hoc cloud infrastructure and associated computing architectures. This will impact at least the following four areas considered in this paper.
Cloud Computing
Faced with continuously increasing scale of data, original back-propagation neural network based machine learning algorithm presents two non-trivial challenges: huge amount of data makes it difficult to maintain both efficiency and accuracy; redundant data aggravates the system workload. 1. Paper. Code.
Cloud Computing: Architecture, Vision, Challenges, Opportunities, and
Cloud computing stands at the forefront of a technological revolution, fundamentally altering the provisioning, utilization, and administration of computing resources. This paper conducts a comprehensive examination of the visionary aspects, obstacles, and possibilities inherent in cloud computing. It delves deep into the foundational principles and distinguishing features of this technology ...
Cloud computing: state-of-the-art and research challenges
In this paper, we present a survey of cloud computing, highlighting its key concepts, architectural principles, state-of-the-art implementation as well as research challenges. The aim of this paper is to provide a better understanding of the design challenges of cloud computing and identify important research directions in this increasingly ...
12 Latest Cloud Computing Research Topics
Virtualizations infrastructure. Software platform. Identity management. Access control. There is some important research direction in Cloud Security in areas such as trusted computing, privacy-preserving models, and information-centric security. These are the following Trending Cloud Computing Research Topics.
[2307.12479] Cloud Cost Optimization: A Comprehensive Review of
Cloud computing has revolutionized the way organizations manage their IT infrastructure, but it has also introduced new challenges, such as managing cloud costs. This paper explores various techniques for cloud cost optimization, including cloud pricing, analysis, and strategies for resource allocation. Real-world case studies of these techniques are presented, along with a discussion of their ...
(PDF) Cloud-Based E-Learning: Using Cloud Computing ...
This paper focuses on the research on the application of cloud computing in e-learning. The aim of this paper is to give an overview of the current state and the impact of the use of cloud ...
Top 15 Cloud Computing Research Topics in 2024
We've compiled 15 important cloud computing research topics that are changing how cloud computing is used. 1. Big Data. Big data refers to the large amounts of data produced by various programs in a very short duration of time. It is quite cumbersome to store such huge and voluminous amounts of data in company-run data centers.
(PDF) Research Paper on Cloud Computing
Student. , M.Sc. I.T., I.C.S. College, Khed, Ratnagri. Abstract: Cloud Computing has come of age later Amazons introduce the first of its kind of cloud services in2006. It is. particularly ...
15+ Cloud Computing Projects With Source Code
Intermediate Cloud Computing Projects with Source Code. 6. System for Online Blood Banking that is hosted in the cloud. 7. Cloud-based conversational Interface. 8. Bookstore on the cloud. 9. Smart Traffic Management System that is cloud-based.
Cloud Computing Research Papers
Resource Management in a Hybrid Cloud Infrastructure. In this paper, a resource management technique is proposed to handle the request of Virtual Machines (VM's) as per the need of users, consisting of resources (mips, vm image size, network bandwidth, number of cpu's) containing cloudlets... more. Download.
Top 22 Cloud Computing Project Ideas in 2024 [Source Code]
Here is a list of curated cloud computing projects for all level skills, one should know in 2024: Cloud-enabled attendance system. Online blood bank system. Online cloud-enabled bookstore system. Data redundancy removal system. Detecting data leaks using SQL injection.
Cloud Computing Project Topics With Abstracts and Base Papers 2024
360. Embark on a journey through innovative research as we unveil M.Tech projects pushing the boundaries of technology. From revolutionizing pavement crack image segmentation with deep learning to addressing healthcare challenges in Mobile Cloud Computing (MCC) through the Modular Encryption Standard (MES), our projects reflect cutting-edge solutions.
NIST Cloud Computing Forensic Reference Architecture
Abstract This document summarizes the research performed by the NIST Cloud Computing Forensic Science Working Group and presents the NIST Cloud Computing Forensic Reference Architecture (CC FRA or FRA), whose goal is to provide support for a cloud system's forensic readiness.
Towards a Novel Privacy-Preserving Distributed Multiparty Data
The intersection of cloud computing, blockchain technology, and the impending era of quantum computing presents a critical juncture for data security. This research addresses the escalating vulnerabilities by proposing a comprehensive framework that integrates Quantum Key Distribution (QKD), CRYSTALS Kyber, and Zero-Knowledge Proofs (ZKPs) for securing data in cloud-based blockchain systems ...
[2408.00731] Litmus: Fair Pricing for Serverless Computing
Serverless computing has emerged as a market-dominant paradigm in modern cloud computing, benefiting both cloud providers and tenants. While service providers can optimize their machine utilization, tenants only need to pay for the resources they use. To maximize resource utilization, these serverless systems co-run numerous short-lived functions, bearing frequent system condition shifts. When ...
Research on Cloud Computing Based on Industrial Internet Platform for
Analysis and Research of Cloud Computing System Instance ICFN '10: Proceedings of the 2010 Second International Conference on Future Networks As a kind of emerging business computational model, Cloud Computing distribute computation task on the resource pool which consists of massive computers, accordingly ,the application systems can gain the ...
New Distributed Cloud- And Network Architecture for True 3D ...
The current 6G NeXt research project [] is exploring the feasibility of using true 3D holography as a case study, establishing criteria for both communication and computing infrastructure.In a future holographic communication service, clients are dispersed throughout the network and engage in collaborative interactions.
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What is Multicloud Security: architecture and ultimate guide
Multicloud is ubiquitous, security is not. Multicloud adoption has accelerated in recent years. In the 2022 Hybrid Cloud Trends report commissioned by Cisco, 82% of IT leaders reported they have adopted hybrid cloud and 58% of organizations use between two and three infrastructure-as-a-service (IaaS) clouds 1.Gartner reported that, by 2023, 40% of all enterprise workloads would be deployed in ...