Journal Title : International Journal of Modern Trends in Engineering and Science


Author’s Name : N Kanimozhi | Gayathri S | Bhuvaneshwari N | Geetha Junnamed

Volume 04 Issue 03 2017

ISSN no:  2348-3121

Page no: 81-83

Abstract – More and more clients would like to store their data on public cloud servers (PCSs). New security problems have to be solved in order to help clients process their data in public cloud. The cloud storage used to check the remote data integrity. It can make the multi-server process to keep the data safely.  The client can store the data in multi-cloud servers. This file is split into blocks using dynamic block generation algorithm. The verifier can check the Remote data integrity at any time. The third party can authenticate the data in the multi-cloud servers. Data integrity checking is done by the verifier. If the signature is verified and it is matched with initial signature, the data are not corrupted and if it is not matched, the data get corrupted by the attacker. Verifier informs corrupted blocks to the cloud. Recovery process will be done by verifier. Again the data can shuffle in the multi-cloud servers. The algorithms used here are base64 algorithm, Message digest algorithm. Dynamic block generation, Verifiable data integrity and string matching are the techniques used. This algorithm can be used for maintaining security and privacy in multi-cloud. Data Recovery is done on integrity checking process when data gets corrupted and also access confidentiality provided by the cloud.

KeywordsProvable Data Possession, Identity-based Cryptography, Distributed Computing


  1. G. Ateniese, R. Burns, R. Curtmola, J. Herring, L. Kissner,
    Z. Peterson, and D. Song, ‘‘Provable Data Possession at
    Untrusted Stores,’’ in Proc. CCS, 2007, pp. 598-609.
  2. G. Ateniese, R. DiPietro, L.V. Mancini, and G. Tsudik, ‘‘Scalable and Efficient Provable Data Possession,’’ in Proc. SecureComm,2008, pp. 1-10.
  3. C.C. Erway, A. Kupcu, C. Papamanthou, and R. Tamassia,
    ‘‘Dynamic Provable Data Possession,’’ in Proc. CCS, 2009,pp. 213-222.
  4. F. Sebe´, J. Domingo-Ferrer, A. Martı´nez-Balleste´, Y. Deswarte and J. Quisquater, ‘‘Efficient Remote Data Integrity Checking in Critical Information Infrastructures,’’ IEEE Trans. Knowl.Data Eng., vol. 20, no. 8, pp. 1034-1038, Aug. 2008.
  5. H.Q.Wang. (2013, Oct./Dec.). Proxy Provable Data Possession in Public Clouds. IEEE Trans. Serv. Comput. [Online]. 6(4), pp. 551-559. Available: http://doi.ieeecomputersociety.org/10.1109/TSC.2012.35.
  6. Y. Zhu, H. Hu, G.J. Ahn, andM. Yu, ‘‘Cooperative Provable Data Possession for Integrity Verification in Multicloud Storage,’’IEEE Trans. Parallel Distrib. Syst., vol. 23, no. 12, pp. 2231-2244,Dec. 2012.
  7. Y. Zhu, H.Wang, Z. Hu, G.J. Ahn, H. Hu, and S.S. Yau, ‘‘Efficient Provable Data Possession for Hybrid Clouds,’’ in Proc. CCS, 2010,pp. 756-758.
  8. R. Curtmola, O. Khan, R. Burns, and G. Ateniese, ‘‘MR-PDP:
    Multiple-Replica Provable Data Possession,’’ in Proc. ICDCS,
    2008, pp. 411-420.
  9. A.F. Barsoum and M.A. Hasan, ‘‘Provable possession and
    replication of data over cloud servers,’’ Centre Appl. Cryptogr.
    Res., Univ. Waterloo, Waterloo, ON, Canada, Rep. 2010/32.
    [Online]. Available: http://www.cacr.math.uwaterloo.ca/
    Tech reports/2010/cacr2010-32.pdf.
  10. Z. Hao and N. Yu, ‘‘A Multiple-Replica Remote Data Possession Checking Protocol with Public Verifiability,’’ in Proc. 2nd Int.Symp. Data, Privacy, E-Comm., 2010, pp. 84-89.
Scroll Up