SCIENCE CHINA Information Sciences, Volume 61 , Issue 12 : 122104(2018) https://doi.org/10.1007/s11432-017-9410-9

Efficient and secure auditing scheme for outsourced big data with dynamicity in cloud

More info
  • ReceivedNov 7, 2017
  • AcceptedFeb 28, 2018
  • PublishedNov 12, 2018


There is no abstract available for this article.


This work was partially supported by National Natural Science Foundation of China (Grant Nos. 61070164, 61272415), Natural Science Foundation of Guangdong Province, China (Grant No. S2012010008767), and Science and Technology Planning Project of Guangdong Province, China (Grant No. 2013B010401015). This work was also supported by the Zhuhai Top Discipline-Information Security.


[1] Demchenko Y, Ngo C, de Laat C, et al. Big security for big data: addressing security challenges for the big data infrastructure. In: Proceedings of Secure Data Management, Trento, 2013. 76--94. Google Scholar

[2] Boyang Wang , Baochun Li , Hui Li . Oruta: privacy-preserving public auditing for shared data in the cloud. 2014, 2: 43-56 CrossRef Google Scholar

[3] Wang C, Chow S S M, Wang Q. Privacy-Preserving Public Auditing for Secure Cloud Storage. 2013, 62: 362-375 CrossRef Google Scholar

[4] Shacham H, Waters B. Compact proofs of retrievability. In: Proceedings of International Conference on the Theory and Application of Cryptology and Information Security, Melbourne, 2008. 90--107. Google Scholar

[5] Wang Q, Wang C, Ren K. Enabling Public Auditability and Data Dynamics for Storage Security in Cloud Computing. 2011, 22: 847-859 CrossRef Google Scholar

[6] Chen L, Zhou S, Huang X. Data dynamics for remote data possession checking in cloud storage. 2013, 39: 2413-2424 CrossRef Google Scholar

[7] Zhang J, Dong Q. Efficient ID-based public auditing for the outsourced data in cloud storage. Inf Sci, 2016, 343: 1-14. Google Scholar

[8] Li J, Zhang L, Liu J K. Privacy-Preserving Public Auditing Protocol for Low-Performance End Devices in Cloud. 2016, 11: 2572-2583 CrossRef Google Scholar

[9] Wang Z, Han Z, Liu J. Public verifiability for shared data in cloud storage with a defense against collusion attacks. 2016, 59: 039101 CrossRef Google Scholar

[10] Wang H, He D, Tang S. Identity-Based Proxy-Oriented Data Uploading and Remote Data Integrity Checking in Public Cloud. 2016, 11: 1165-1176 CrossRef Google Scholar

[11] Yu Y, Au M H, Ateniese G. Identity-Based Remote Data Integrity Checking With Perfect Data Privacy Preserving for Cloud Storage. 2017, 12: 767-778 CrossRef Google Scholar

[12] Zhang R, Ma H, Lu Y. Provably secure cloud storage for mobile networks with less computation and smaller overhead. 2017, 60: 122104 CrossRef Google Scholar

[13] Sookhak M, Gani A, Khan M K. WITHDRAWN: Dynamic remote data auditing for securing big data storage in cloud computing. 2017, 380: 101-116 CrossRef Google Scholar

[14] Schwarz T S J, Miller E L. Store, forget, and check: Using algebraic signatures to check remotely administered storage. In: Proceedings of the 26th IEEE International Conference on Distributed Computing Systems, Lisboa, 2006. 12--21. Google Scholar

[15] Chen L. Using algebraic signatures to check data possession in cloud storage. 2013, 29: 1709-1715 CrossRef Google Scholar

[16] Sookhak M, Akhunzada A, Gani A, et al. Towards dynamic remote data auditing in computational clouds. Sci World J, 2014, 2014: 269357. Google Scholar

[17] Luo Y C, Fu S J, Xu M, et al. Enable data dynamics for algebraic signatures based remote data possession checking in the cloud storage. China Commun, 2014, 11: 114-124. Google Scholar

[18] Litwin W, Schwarz T. Algebraic signatures for scalable distributed data structures. In: Proceedings of the 20th International Conference on Data Engineering, Boston, 2004. 412-423. Google Scholar

[19] Ateniese G, Burns R, Curtmola R, et al. Provable data possession at untrusted stores. In: Proceedings of the 14th ACM Conference on Computer and Communications Security, Alexandria, 2007. 598--609. Google Scholar

[20] Juels A, Kaliski B S. PORs: proofs of retrievability for large files. In: Proceedings of ACM Conference on Computer and Communications Security, Alexandria, 2007. 584--597. Google Scholar

[21] Yu Y, Zhang Y, Ni J. Remote data possession checking with enhanced security for cloud storage. 2015, 52: 77-85 CrossRef Google Scholar

[22] Ateniese G, Pietro R D, Mancini L V, et al. Scalable and efficient provable data possession. In: Proceedings of the 4th International Conference on Security and Privacy in Communication Networks, Istanbul, 2008. 1--10. Google Scholar

[23] Erway C C, Papamanthou C, Tamassia R. Dynamic provable data possession. ACM Trans Inf Syst Secur, 2009, 17: 213-222. Google Scholar

[24] Cash D, Küp?ü A, Wichs D. Dynamic Proofs of Retrievability Via Oblivious RAM. 2017, 30: 22-57 CrossRef Google Scholar

[25] Yang K, Jia X. An Efficient and Secure Dynamic Auditing Protocol for Data Storage in Cloud Computing. 2013, 24: 1717-1726 CrossRef Google Scholar

[26] Shen J, Shen J, Chen X. An Efficient Public Auditing Protocol With Novel Dynamic Structure for Cloud Data. 2017, 12: 2402-2415 CrossRef Google Scholar

[27] Thangavel M, Varalakshmi P, Preethi T, et al. A review on public auditing in cloud environment. In: Proceedings of Information Communication and Embedded Systems, Chennai, 2016. 1-6. Google Scholar

[28] Ateniese G, Burns R, Curtmola R, et al. Remote data checking using provable data possession. ACM Trans Inf Syst Secur, 2011, 14: 1165--1182. Google Scholar

[29] Ren S Q, Tan B H M, Sundaram S. Secure searching on cloud storage enhanced by homomorphic indexing. 2016, 65: 102-110 CrossRef Google Scholar

[30] Ade-Ibijola A O. A simulated enhancement of Fisher-Yates algorithm for shuffling in virtual card games using domain-specific data structures. Int J Comput Appl, 2012, 54: 24-28. Google Scholar

[31] Barsoum A, Hasan A. On Verifying Dynamic Multiple Data Copies over Cloud Servers. IACR Cryptology Eprint Arch, 2011, 2011: 447-476. Google Scholar

[32] Barsoum A, Hasan A. Enabling Dynamic Data and Indirect Mutual Trust for Cloud Computing Storage Systems. 2013, 24: 2375-2385 CrossRef Google Scholar

  • Figure 1

    (Color online) The architecture of outsourced big data auditing in cloud storage.

  • Figure 2

    The process of the outsourced big data auditing scheme.

  • Figure 3

    (Color online) Computation cost for 16 blocks $\times$ 16 sectors.

    Server Verifier Verifier Third-
    Scheme Cryptography computation computation Communication storage Dynamic party
    based on complexity complexity complexity complexity auditing auditor
    PDP [19] Public-key $O(1)$ $O(1)$ $O(1)$ $O(1)$ No No
    DPDP [23] Public-key $O(\log~n)$ $O(\log~n)$ $O(\log~n)$ $O(1)$ Yes No
    PADD [5] Public-key $O(\log~n)$ $O(\log~n)$ $O(\log~n)$ $O(1)$ Yes Yes
    RDPC [21] Symmetric-key $O(\log~n)$ $O(\log~n)$ $O(\log~n)$ $O(1)$ No No
    Our basic scheme Symmetric-key $O(1)$ $O(1)$ $O(1)$ $O(1)$ No Yes
    Size of Time for Time for Time for Time for
    sectors (bits) Setup (ms) TagBlock (ms) Proof (ms) Verification (ms)
    1024 2.81 1.65 1.59
    2048 $\approx0.32$ 3.03 1.68 1.63
    4096 3.19 1.69 1.65
    8192 3.46 1.72 1.69

Copyright 2020  CHINA SCIENCE PUBLISHING & MEDIA LTD.  中国科技出版传媒股份有限公司  版权所有

京ICP备14028887号-23       京公网安备11010102003388号