Efficient privacy preserving integrity checking model for cloud data storage security

Subha, T.D.; Jayashri, S.

doi:10.1109/icoac.2017.7951745

Cited by 17 publications

(20 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The following are the studies that were used to create the set of privacy-preserving attributes. 6,[9][10][11][12][13][14]16,26,29, This article combines the most modern and well-known privacy attributes that are employed for Cloud data storage. These attributes are thought to represent the most recent discoveries of cyber security specialists in the sector.…”

Section: The Taxonomy Of Privacy-preserving Attributes For the Cloud ...mentioning

confidence: 99%

“…The decryption method restores the original format (plain text) of the encrypted data. 12,13,44 Decryption algorithms are used in CC to obtain encrypted items from the Cloud repositories (Cloud storage) via requests from specified users. To obtain access to the required data, users must have the appropriate credentials and the decryption key.…”

Section: Data Auditing Approachesmentioning

confidence: 99%

“…10 To prevent malevolent attackers from tampering with data, the zero-knowledge shuffle correctness proof test was introduced by Yuan et al 11 Traditional tests, such as storage, time, and cost analyses, were used by several authors. [12][13][14] Other tests include a user accountability test to determine whether Cloud consumers are trustable, a data confidentiality test to determine whether data is transmitted securely between Cloud entities without alteration or theft attempts, and a test to determine whether the third-party authority is leaking data. 11 Moreover, SQL operations were used to compute the average execution time in web applications during the compatibility test.…”

Section: Test Appliedmentioning

confidence: 99%

“…9 However, the bulk of these techniques was created to achieve certain goals, such as improving user identity, data integrity, and data analysis, among others. [10][11][12][13][14] As a result, a comprehensive framework that can fulfill various privacy-preserving attributes is still a major demand. 7,15,16 The primary focus of this study is to provide a framework that meets different attributes of privacy-preserving while also introducing innovation in data storage and retrieval on Cloud storage.…”

mentioning

confidence: 99%

See 3 more Smart Citations

Enhancing privacy‐preserving mechanisms in Cloud storage: A novel conceptual framework

Mishra,

Jabar,

Alzoubi

et al. 2023

Concurrency and Computation

View full text Add to dashboard Cite

SummaryData privacy is critical for users who want to use Cloud storage services. There is a significant focus on Cloud service providers to address this need. However, in the evolving dynamic cyber‐space, privacy infractions are rising and pose threats to Cloud storage infrastructures. Several studies developed various models and techniques to ensure the privacy of Cloud storage contents. However, these models came with several shortages in the privacy‐preserving attributes they cover. Thus, this article identified a comprehensive set of Cloud data storage privacy‐preserving attributes to propose a flexible and efficient framework to handle the privacy problem. This framework uses a multi‐layer encryption storage structure and a one‐time password authentication technique. The findings of this article intend to help future communities to enhance existing techniques or develop new research‐based practical alternatives. Since Cloud computing is a rapidly growing technology, new privacy vulnerabilities emerge daily. Future research might confirm the findings of this article and test the suggested framework in different contexts.

show abstract

Section: The Taxonomy Of Privacy-preserving Attributes For the Cloud ...mentioning

confidence: 99%

Section: Data Auditing Approachesmentioning

confidence: 99%

Section: Test Appliedmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Enhancing privacy‐preserving mechanisms in Cloud storage: A novel conceptual framework

Mishra,

Jabar,

Alzoubi

et al. 2023

Concurrency and Computation

View full text Add to dashboard Cite

show abstract

“…Once the data or database is shifted from local systems to the cloud, CSP takes the charge and starts managing data [4]. The initial data owner does not have control over the data at this stage, which poses a major security concern.…”

Section: Introductionmentioning

confidence: 99%

Integrity Monitoring with ECMRSA Algorithm for Cloud Data Outsourcing

Thắng¹,

Pham²

2020

IJEIT

View full text Add to dashboard Cite

With its on-demand technology, cloud computing has advanced to allow vast volumes of data to be interchanged via cloud services. Scalable cloud services that store confidential data on cloud storage servers are therefore critical to the complex management of a number of problem fields: security, privacy, data sharing and cloud server integrity. In addition, in this expanded environment, validity and control of access to data should be retained. One of the core principles for cloud encryption is abe. An interest in this research is the auditing of data or integrity tests for secure cloud storage. The data audit approach allows an auditor to verify the consistency of the data files and submit the data owner's verification report, without understanding the files. This paper offers an RSA modified elliptic curve (ECMRSA) and an algorithm modified to md5 for the purpose of verifying the integrity of cloud data, to upload the encrypted data files of data users or proprietors to the cloud data server and send a request for a third-party audit to the auditor. On behalf of data holders, a third-party auditor (TPA) is called by the data server to ensure the file is credible. The auditor sends the audit report to the owner following maintenance of the data file accuracy. A public key coding scheme with homomorphic algorithms that produces a digital file signature or hash values for coded files is included in the proposed audit algorithm.

show abstract

Deficiencies of Compliancy for Data and Storage

Goodman

Rowland

2020

Advances in Intelligent Systems and Computing

View full text Add to dashboard Cite

Efficient privacy preserving integrity checking model for cloud data storage security

Cited by 17 publications

References 14 publications

Enhancing privacy‐preserving mechanisms in Cloud storage: A novel conceptual framework

Enhancing privacy‐preserving mechanisms in Cloud storage: A novel conceptual framework

Integrity Monitoring with ECMRSA Algorithm for Cloud Data Outsourcing

Deficiencies of Compliancy for Data and Storage

Contact Info

Product

Resources

About