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Towards dynamic remote data auditing in computational clouds.

Sookhak M, Akhunzada A, Gani A, Khurram Khan M, Anuar NB - ScientificWorldJournal (2014)

Bottom Line: We propose an effectual RDA technique based on algebraic signature properties for cloud storage system and also present a new data structure capable of efficiently supporting dynamic data operations like append, insert, modify, and delete.Moreover, this data structure empowers our method to be applicable for large-scale data with minimum computation cost.The comparative analysis with the state-of-the-art RDA schemes shows that the proposed scheme is secure and highly efficient in terms of the computation and communication overhead on the auditor and server.

View Article: PubMed Central - PubMed

Affiliation: Center for Mobile Cloud Computing Research (C4MCCR), University of Malaya, 50603 Kuala Lumpur, Malaysia.

ABSTRACT
Cloud computing is a significant shift of computational paradigm where computing as a utility and storing data remotely have a great potential. Enterprise and businesses are now more interested in outsourcing their data to the cloud to lessen the burden of local data storage and maintenance. However, the outsourced data and the computation outcomes are not continuously trustworthy due to the lack of control and physical possession of the data owners. To better streamline this issue, researchers have now focused on designing remote data auditing (RDA) techniques. The majority of these techniques, however, are only applicable for static archive data and are not subject to audit the dynamically updated outsourced data. We propose an effectual RDA technique based on algebraic signature properties for cloud storage system and also present a new data structure capable of efficiently supporting dynamic data operations like append, insert, modify, and delete. Moreover, this data structure empowers our method to be applicable for large-scale data with minimum computation cost. The comparative analysis with the state-of-the-art RDA schemes shows that the proposed scheme is secure and highly efficient in terms of the computation and communication overhead on the auditor and server.

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Comparison of computation cost under different number of update requests.
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Related In: Results  -  Collection


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fig8: Comparison of computation cost under different number of update requests.

Mentions: We conduct the experiments for updating an outsourced file (F) with length 1 GB, including 125,000 data blocks, and demonstrate the efficiency of the proposed scheme in Figure 8, where the numbers of updated (inserted or deleted) blocks are increasing from 100 to 1000 with intervals of 8. To insert or delete a block in the Wang scheme, the auditor needs to find the position of the block (i) in the MHT tree. Moreover, inserting or deleting a block needs to recalculate the hash of the root each time that incurs the huge computation overhead on the auditor. Similarly, in the Yang method, after finding the position of the block (i), as a precondition, the auditor has to shift the remaining (n − i) blocks for every insert or delete operations. Subsequently, repeating this process multiple (100–1000) times results in a significant computation overhead on the auditor. The proposed method considers 10 DCTs with size 12500 instead of a single array with size 125000 in the Yang scheme. Consequently, the number of shifts reduced in our method results in the minimum computation overhead on the client side. Figure 8 shows the performance in terms of computation cost under different number of update (insert or delete) operations. The analysis of the results shows the efficiency of our scheme.


Towards dynamic remote data auditing in computational clouds.

Sookhak M, Akhunzada A, Gani A, Khurram Khan M, Anuar NB - ScientificWorldJournal (2014)

Comparison of computation cost under different number of update requests.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4121005&req=5

fig8: Comparison of computation cost under different number of update requests.
Mentions: We conduct the experiments for updating an outsourced file (F) with length 1 GB, including 125,000 data blocks, and demonstrate the efficiency of the proposed scheme in Figure 8, where the numbers of updated (inserted or deleted) blocks are increasing from 100 to 1000 with intervals of 8. To insert or delete a block in the Wang scheme, the auditor needs to find the position of the block (i) in the MHT tree. Moreover, inserting or deleting a block needs to recalculate the hash of the root each time that incurs the huge computation overhead on the auditor. Similarly, in the Yang method, after finding the position of the block (i), as a precondition, the auditor has to shift the remaining (n − i) blocks for every insert or delete operations. Subsequently, repeating this process multiple (100–1000) times results in a significant computation overhead on the auditor. The proposed method considers 10 DCTs with size 12500 instead of a single array with size 125000 in the Yang scheme. Consequently, the number of shifts reduced in our method results in the minimum computation overhead on the client side. Figure 8 shows the performance in terms of computation cost under different number of update (insert or delete) operations. The analysis of the results shows the efficiency of our scheme.

Bottom Line: We propose an effectual RDA technique based on algebraic signature properties for cloud storage system and also present a new data structure capable of efficiently supporting dynamic data operations like append, insert, modify, and delete.Moreover, this data structure empowers our method to be applicable for large-scale data with minimum computation cost.The comparative analysis with the state-of-the-art RDA schemes shows that the proposed scheme is secure and highly efficient in terms of the computation and communication overhead on the auditor and server.

View Article: PubMed Central - PubMed

Affiliation: Center for Mobile Cloud Computing Research (C4MCCR), University of Malaya, 50603 Kuala Lumpur, Malaysia.

ABSTRACT
Cloud computing is a significant shift of computational paradigm where computing as a utility and storing data remotely have a great potential. Enterprise and businesses are now more interested in outsourcing their data to the cloud to lessen the burden of local data storage and maintenance. However, the outsourced data and the computation outcomes are not continuously trustworthy due to the lack of control and physical possession of the data owners. To better streamline this issue, researchers have now focused on designing remote data auditing (RDA) techniques. The majority of these techniques, however, are only applicable for static archive data and are not subject to audit the dynamically updated outsourced data. We propose an effectual RDA technique based on algebraic signature properties for cloud storage system and also present a new data structure capable of efficiently supporting dynamic data operations like append, insert, modify, and delete. Moreover, this data structure empowers our method to be applicable for large-scale data with minimum computation cost. The comparative analysis with the state-of-the-art RDA schemes shows that the proposed scheme is secure and highly efficient in terms of the computation and communication overhead on the auditor and server.

Show MeSH