1 Introduction
2 Related works
3 System model
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The Cloud Service Provider (S): a third party who provides storage services to the data owners. The data owners can upload their data blocks to the storage space provide by S.
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The data owner (D): is an enterprise or an individual who outsources the data in the cloud. The D will divide the file into fixed sized data blocks and generate multiple replicas for the data blocks
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The User (U): who has limited access rights to share or use the data block stored with the S.The User U will possess the valid decryption key to access all the encrypted data blocks.
4 Integrity preserving storage model with replication support
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If file grows in its size, more blocks are needed to represent the file. Even in this case the performance of our approach remains the same. It does not degrade like the traditional binary tree structured merkle tree. This is because all the blocks are maintained at leaf node and all the nodes are at equi-distance from root. In addition, if there is any overflow, it automatically re-organizes the structure.
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Even though insertion and deletion are little complicated, it does not leads to any significant increase in computation time.
5 Tweak based secure PDP-R scheme
5.1 Performance of Tweak based secure PDP-R scheme
6 Algorithms for dynamic data operations support
S/N | Data owner | Cloud service provider |
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1 | Generates a random key r and s \(\in _{\mathrm{R}}\) Z\(_{\mathrm{N}}\) | |
2 | Computes g\(_{\mathrm{s}}\) = g\(^{\mathrm{s}}\) mod N | |
3 | send r, g\(_{\mathrm{s}}\) to the remote cloud server | |
4 | Generates random coefficients {aj = PRF(j)}1 \(\le \) j \(\le \) m | |
5 | Computes R = (g\(_{\mathrm{s}})\) . \(\sum \)m j=1 aj .bj mod N | |
6 | send R to the data owner | |
7 | Generates a set of random coefficients {a\(_{\mathrm{j}}\) = f\(_{\mathrm{r}}\)(j)}\(_{1\le \mathrm{j}\le \mathrm{m} }\) | |
8 | Computes (T\(^{\mathrm{aj}}\) mod N) mod N | |
9 | Computes R\(^\prime \) = P \(^{s}\) mod N | |
10 | Checks R\(^\prime \) ?= R |
Performance parameters | Basic PDP scheme | PDP schemes with remote integrity checks | PDP Schemes at untrusted sources | Our scheme |
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Data owner computation overhead | Linear with the size of the file | O(m) | O(m) | O(1) |
CSP computation overhead | Linear with the size of the file | O(n) | O(n) | o(1) |
Data owner storage overhead | NO | NO | NO | NO |
CSP storage overhead | O(m) | O(m) | O(m) | O(m) |
No of challenges that can be made | Unbounded | Unbounded | Unbounded | Unbounded |
Probabilistic/deterministic approach | Deterministic | Both | Probabilistic | Probabilistic |