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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| Format: | Book Section |
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Springer Science and Business Media Deutschland GmbH
2022
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| _version_ | 1796866851541614592 |
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| 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. |
| collection | ePrints |
| 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. |
| first_indexed | 2024-03-05T21:18:23Z |
| format | Book Section |
| id | utm.eprints-100301 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T21:18:23Z |
| publishDate | 2022 |
| publisher | Springer Science and Business Media Deutschland GmbH |
| record_format | dspace |
| spelling | utm.eprints-1003012023-04-04T06:58:22Z http://eprints.utm.my/100301/ 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. 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. Springer Science and Business Media Deutschland GmbH 2022 Book Section PeerReviewed Ibrahim, Shamiel H. and Md. Sirat, Maheyzah and Elbakri, Widad M. M. (2022) Data integrity for dynamic big data in cloud storage: A comprehensive review and critical issues. In: Emerging Technologies in Computing 5th EAI International Conference, iCETiC 2022, Chester, UK, August 15-16, 2022, Proceedings. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications, 463 (NA). Springer Science and Business Media Deutschland GmbH, Cham, Switzerland, pp. 67-81. ISBN 978-303125160-3 http://dx.doi.org/10.1007/978-3-031-25161-0_5 DOI : 10.1007/978-3-031-25161-0_5 |
| spellingShingle | 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 |
| title | 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_short | 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 |
| topic | QA75 Electronic computers. Computer science |
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