Data integrity for dynamic big data in cloud storage: a comprehensive review and critical issues

Cloud storage services provide vast storage space to solve the bottleneck of the data generated by different big data applications. However, the nature of big data in terms of its massive volume and rapid velocity, needs to be considered when designing data integrity schemes to provide security assu...

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Main Authors: Ibrahim, Shamiel H., Md. Sirat, Maheyzah, Elbakri, Widad M. M.
Format: Conference or Workshop Item
Published: 2023
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Online Access:http://eprints.utm.my/108183/
http://dx.doi.org/10.1007/978-3-031-25161-0_5
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Institution: Universiti Teknologi Malaysia
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spelling my.utm.1081832024-10-20T08:05:32Z http://eprints.utm.my/108183/ Data integrity for dynamic big data in cloud storage: a comprehensive review and critical issues Ibrahim, Shamiel H. Md. Sirat, Maheyzah Elbakri, Widad M. M. QA Mathematics QA75 Electronic computers. Computer science Cloud storage services provide vast storage space to solve the bottleneck of the data generated by different big data applications. However, the nature of big data in terms of its massive volume and rapid velocity, needs to be considered when designing data integrity schemes to provide security assurance for data stored in the cloud. The state of the art of data integrity in the cloud includes two primary schemes: (i) Proof of Retrievability (POR) and (ii) Provable Data Possession. Both techniques are designed to achieve the same goal in ensuring data integrity of outsourced data in cloud storage; However, PoR varies from PDP by error-correcting feature to retrieve the damaged outsourced data. This paper focuses on the proof of data retrievability technique (POR) for dynamic data. Dynamic data is defined as data under different update operations. The paper surveys the state of the art data integrity techniques for cloud storage (CS) and previous work on basic requirements for an effective data integrity technique for big data applications. Methods used to provide dynamic PoR are discussed before summarizing the classification of the POR state-of-the-art. The recently proposed techniques and their limitations are also discussed with issues to consider for future POR scheme design. 2023 Conference or Workshop Item PeerReviewed Ibrahim, Shamiel H. and Md. Sirat, Maheyzah and Elbakri, Widad M. M. (2023) Data integrity for dynamic big data in cloud storage: a comprehensive review and critical issues. In: 5th EAI International Conference on Emerging Technologies in Computing, iCETiC 2022, 15 August 2022 - 16 August 2022, Chester, Cheshire, England. http://dx.doi.org/10.1007/978-3-031-25161-0_5
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA Mathematics
QA75 Electronic computers. Computer science
spellingShingle QA Mathematics
QA75 Electronic computers. Computer science
Ibrahim, Shamiel H.
Md. Sirat, Maheyzah
Elbakri, Widad M. M.
Data integrity for dynamic big data in cloud storage: a comprehensive review and critical issues
description Cloud storage services provide vast storage space to solve the bottleneck of the data generated by different big data applications. However, the nature of big data in terms of its massive volume and rapid velocity, needs to be considered when designing data integrity schemes to provide security assurance for data stored in the cloud. The state of the art of data integrity in the cloud includes two primary schemes: (i) Proof of Retrievability (POR) and (ii) Provable Data Possession. Both techniques are designed to achieve the same goal in ensuring data integrity of outsourced data in cloud storage; However, PoR varies from PDP by error-correcting feature to retrieve the damaged outsourced data. This paper focuses on the proof of data retrievability technique (POR) for dynamic data. Dynamic data is defined as data under different update operations. The paper surveys the state of the art data integrity techniques for cloud storage (CS) and previous work on basic requirements for an effective data integrity technique for big data applications. Methods used to provide dynamic PoR are discussed before summarizing the classification of the POR state-of-the-art. The recently proposed techniques and their limitations are also discussed with issues to consider for future POR scheme design.
format Conference or Workshop Item
author Ibrahim, Shamiel H.
Md. Sirat, Maheyzah
Elbakri, Widad M. M.
author_facet Ibrahim, Shamiel H.
Md. Sirat, Maheyzah
Elbakri, Widad M. M.
author_sort Ibrahim, Shamiel H.
title Data integrity for dynamic big data in cloud storage: a comprehensive review and critical issues
title_short Data integrity for dynamic big data in cloud storage: a comprehensive review and critical issues
title_full Data integrity for dynamic big data in cloud storage: a comprehensive review and critical issues
title_fullStr Data integrity for dynamic big data in cloud storage: a comprehensive review and critical issues
title_full_unstemmed Data integrity for dynamic big data in cloud storage: a comprehensive review and critical issues
title_sort data integrity for dynamic big data in cloud storage: a comprehensive review and critical issues
publishDate 2023
url http://eprints.utm.my/108183/
http://dx.doi.org/10.1007/978-3-031-25161-0_5
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