76 research outputs found
Certificateless Public Auditing Protocol with Constant
To provide the integrity of outsourced data in the cloud storage services, many public auditing schemes which allow a user to check the integrity of the outsourced data have been proposed. Since most of the schemes are constructed on Public Key Infrastructure (PKI), they suffer from several concerns like management of certificates. To resolve the problems, certificateless public auditing schemes also have been studied in recent years. In this paper, we propose a certificateless public auditing scheme which has the constant-time verification algorithm. Therefore, our scheme is more efficient than previous certificateless public auditing schemes. To prove the security of our certificateless public auditing scheme, we first define three formal security models and prove the security of our scheme under the three security models
Data Auditing and Security in Cloud Computing: Issues, Challenges and Future Directions
Cloud computing is one of the significant development that utilizes progressive computational power and upgrades data distribution and data storing facilities. With cloud information services, it is essential for information to be saved in the cloud and also distributed across numerous customers. Cloud information repository is involved with issues of information integrity, data security and information access by unapproved users. Hence, an autonomous reviewing and auditing facility is necessary to guarantee that the information is effectively accommodated and used in the cloud. In this paper, a comprehensive survey on the state-of-art techniques in data auditing and security are discussed. Challenging problems in information repository auditing and security are presented. Finally, directions for future research in data auditing and security have been discussed
Data auditing and security in cloud computing: issues, challenges and future directions
Cloud computing is one of the significant development that utilizes progressive computational power and
upgrades data distribution and data storing facilities. With cloud information services, it is essential for
information to be saved in the cloud and also distributed across numerous customers. Cloud information
repository is involved with issues of information integrity, data security and information access by unapproved
users. Hence, an autonomous reviewing and auditing facility is necessary to guarantee that the information is
effectively accommodated and used in the cloud. In this paper, a comprehensive survey on the state-of-art
techniques in data auditing and security are discussed. Challenging problems in information repository auditing
and security are presented. Finally, directions for future research in data auditing and security have been
discusse
An extensive research survey on data integrity and deduplication towards privacy in cloud storage
Owing to the highly distributed nature of the cloud storage system, it is one of the challenging tasks to incorporate a higher degree of security towards the vulnerable data. Apart from various security concerns, data privacy is still one of the unsolved problems in this regards. The prime reason is that existing approaches of data privacy doesn't offer data integrity and secure data deduplication process at the same time, which is highly essential to ensure a higher degree of resistance against all form of dynamic threats over cloud and internet systems. Therefore, data integrity, as well as data deduplication is such associated phenomena which influence data privacy. Therefore, this manuscript discusses the explicit research contribution toward data integrity, data privacy, and data deduplication. The manuscript also contributes towards highlighting the potential open research issues followed by a discussion of the possible future direction of work towards addressing the existing problems
Group Based Secure Sharing of Cloud Data with Provable Data Freshness
With cloud computing technology it is realized that data can be outsource and such data can also be shared among users of cloud. However, the data outsourced to cloud might be subjected to integrity problems due to the problems in the underlying hardware or software errors. Human errors also may contribute to the integrity problems. Many techniques came into existence in order to ensure data integrity. Most of the techniques have some sort of auditing. Public auditing schemes meant for data integrity of shared data might disclose confidential information. To overcome this problem, recently, Wang et al. proposed a novel approach that supports public auditing and also do not disclose confidential information. They exploited ring signatures that are used to compute verification metadata on the fly in order to audit the correctness of shared data. The public verifiers do not know the identity of the signer. It does mean that the verifier can verify data without knowing the identity of the signer. However, this scheme does not consider the freshness of data which is very important in cloud services. Obtaining latest copy of data is very important to avoid stale data access in cloud. Towards this end, in this paper, we proposed an algorithm for ensuring freshness of the data while retrieving the outsourced data in multi-user environment. Our empirical results revealed that the proposed algorithm is efficient.
DOI: 10.17762/ijritcc2321-8169.15065
Light-Weight Accountable Privacy Preserving Protocol in Cloud Computing Based on a Third-Party Auditor
Cloud computing is emerging as the next disruptive utility paradigm [1]. It provides extensive storage capabilities and an environment for application developers through virtual machines. It is also the home of software and databases that are accessible, on-demand. Cloud computing has drastically transformed the way organizations, and individual consumers access and interact with Information Technology. Despite significant advancements in this technology, concerns about security are holding back businesses from fully adopting this promising information technology trend. Third-party auditors (TPAs) are becoming more common in cloud computing implementations. Hence, involving auditors comes with its issues such as trust and processing overhead. To achieve productive auditing, we need to (1) accomplish efficient auditing without requesting the data location or introducing processing overhead to the cloud client; (2) avoid introducing new security vulnerabilities during the auditing process. There are various security models for safeguarding the CCs (Cloud Client) data in the cloud. The TPA systematically examines the evidence of compliance with established security criteria in the connection between the CC and the Cloud Service Provider (CSP). The CSP provides the clients with cloud storage, access to a database coupled with services. Many security models have been elaborated to make the TPA more reliable so that the clients can trust the third-party auditor with their data. Our study shows that involving a TPA might come with its shortcomings, such as trust concerns, extra overhead, security, and data manipulation breaches; as well as additional processing, which leads to the conclusion that a lightweight and secure protocol is paramount to the solution. As defined in [2] privacy-preserving is making sure that the three cloud stakeholders are not involved in any malicious activities coming from insiders at the CSP level, making sure to remediate to TPA vulnerabilities and that the CC is not deceitfully affecting other clients. In our survey phase, we have put into perspective the privacy-preserving solutions as they fit the lightweight requirements in terms of processing and communication costs, ending up by choosing the most prominent ones to compare with them our simulation results. In this dissertation, we introduce a novel method that can detect a dishonest TPA: The Light-weight Accountable Privacy-Preserving (LAPP) Protocol. The lightweight characteristic has been proven simulations as the minor impact of our protocol in terms of processing and communication costs. This protocol determines the malicious behavior of the TPA. To validate our proposed protocol’s effectiveness, we have conducted simulation experiments by using the GreenCloud simulator. Based on our simulation results, we confirm that our proposed model provides better outcomes as compared to the other known contending methods
Data storage security and privacy in cloud computing: A comprehensive survey
Cloud Computing is a form of distributed computing wherein
resources and application platforms are distributed over the
Internet through on demand and pay on utilization basis. Data
Storage is main feature that cloud data centres are provided to
the companies/organizations to preserve huge data. But still
few organizations are not ready to use cloud technology due
to lack of security. This paper describes the different
techniques along with few security challenges, advantages and
also disadvantages. It also provides the analysis of data
security issues and privacy protection affairs related to cloud
computing by preventing data access from unauthorized users,
managing sensitive data, providing accuracy and consistency
of data store
Revealing the Landscape of Privacy-Enhancing Technologies in the Context of Data Markets for the IoT: A Systematic Literature Review
IoT data markets in public and private institutions have become increasingly
relevant in recent years because of their potential to improve data
availability and unlock new business models. However, exchanging data in
markets bears considerable challenges related to disclosing sensitive
information. Despite considerable research focused on different aspects of
privacy-enhancing data markets for the IoT, none of the solutions proposed so
far seems to find a practical adoption. Thus, this study aims to organize the
state-of-the-art solutions, analyze and scope the technologies that have been
suggested in this context, and structure the remaining challenges to determine
areas where future research is required. To accomplish this goal, we conducted
a systematic literature review on privacy enhancement in data markets for the
IoT, covering 50 publications dated up to July 2020, and provided updates with
24 publications dated up to May 2022. Our results indicate that most research
in this area has emerged only recently, and no IoT data market architecture has
established itself as canonical. Existing solutions frequently lack the
required combination of anonymization and secure computation technologies.
Furthermore, there is no consensus on the appropriate use of blockchain
technology for IoT data markets and a low degree of leveraging existing
libraries or reusing generic data market architectures. We also identified
significant challenges remaining, such as the copy problem and the recursive
enforcement problem that-while solutions have been suggested to some extent-are
often not sufficiently addressed in proposed designs. We conclude that
privacy-enhancing technologies need further improvements to positively impact
data markets so that, ultimately, the value of data is preserved through data
scarcity and users' privacy and businesses-critical information are protected.Comment: 49 pages, 17 figures, 11 table
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