Advertisement

A Survey on Various Integrity Verification Schemes on the Data Outsourced to Cloud Storage

  • S. Milton GaneshEmail author
  • S. P. Manikandan
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1116)

Abstract

The cloud storage is available on-demand, flexible resource provisioning with pay-as-you-go pricing methodologies powered by data centers and virtualization technologies. One of the major applications from cloud service providers is that of the cloud storage. The service providers are ensuring reliability in such a way that, if one server crashes or currently down, a backup server is some other location facilitates continued service-provisioning for the customers. In such an environment, the customers data are stored in a single cloud server or multiple cloud servers. In the current trend, the data has become more valued than the hardware. Hence, verification of data uploaded to the cloud servers at regular intervals is important. This research work strives to provide a wide range of methods which offer this integrity verification service with their merits and demerits.

Keywords

Remote data Provable data possession Integrity verification Cloud storage 

References

  1. 1.
    Armbrust, M., et al.: A view of cloud computing. Commun. ACM 53, 50–58 (2010)CrossRefGoogle Scholar
  2. 2.
    Ekanayake, J., Fox, G.: High performance parallel computing with clouds and cloud technologies. In: Avresky, D.R., Diaz, M., Bode, A., Ciciani, B., Dekel, E. (eds.) CloudComp 2009. LNICSSTE, vol. 34, pp. 20–38. Springer, Heidelberg (2010).  https://doi.org/10.1007/978-3-642-12636-9_2CrossRefGoogle Scholar
  3. 3.
    Keahey, K., Foster, I., Freeman, T., Zhang, X.: VirtualWorkspaces: achieving quality of service and quality of life in the grid. Sci. Program. J. 13(4), 265–276 (2005)Google Scholar
  4. 4.
    Foster, I.: The anatomy of the grid: enabling scalable virtual organizations. In: Sakellariou, R., Gurd, J., Freeman, L., Keane, J. (eds.) Euro-Par 2001. LNCS, vol. 2150, pp. 1–4. Springer, Heidelberg (2001).  https://doi.org/10.1007/3-540-44681-8_1CrossRefGoogle Scholar
  5. 5.
    Gavrilovska, A., et al.: High-performance hypervisor architectures: virtualization in HPC systems. In: 1st Workshop on System-Level Virtualization for High Performance Computing (2007)Google Scholar
  6. 6.
    Li, Z., He, Q., Zhang, X.: Study on cloud storage system based on distributed storage systems. In: International Conference on Computational and Information Sciences, Chengdu, China, pp. 1332–1335 (2010)Google Scholar
  7. 7.
    Gu, Y., Grossman, R.L.: Sector and Sphere: the design and implementation of a high-performance data cloud. Philos. Trans. R. Soc. 367, 2429–2445 (2009)CrossRefGoogle Scholar
  8. 8.
    Yurukonda, N., ThirumalaRao, B.: A study on data storage security issues in cloud computing. J. Procedia Comput. Sci. 92, 128–135 (2016)CrossRefGoogle Scholar
  9. 9.
    Balduzzi, M., Zaddach, J., Balzarotti, D., Kirda, E., Loureiro, S.: A security analysis of amazon’s elastic compute cloud service. In: Proceedings of the 27th Annual ACM Symposium on Applied Computing, Trento, Italy, pp. 1427–1434 (2012)Google Scholar
  10. 10.
    Yang, K., Xia, X.: An efficient and secure dynamic auditing protocol for data storage in the cloud computing. IEEE Trans. Parallel Distrib. Syst. 24(9), 1717–1726 (2013)CrossRefGoogle Scholar
  11. 11.
    Liu, C., Yang, C., Zhang, X., Chen, J.: External integrity verification for outsourced big data in cloud and IoT: a big picture. Future Gener. Comput. Syst. J. 49, 58–67 (2015)CrossRefGoogle Scholar
  12. 12.
    Shin, S., Kwon, T.: A survey of public provable data possession schemes with batch verification in cloud storage. J. Internet Serv. Inf. Secur. 5(3), 37–47 (2015)Google Scholar
  13. 13.
    Rani, R.S.M., Ragha, L.: Dynamic public data auditing schemes on cloud: a survey. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 8(1), 76–78 (2018)CrossRefGoogle Scholar
  14. 14.
    Zhou, L., Fu, A., Yu, S., Su, M., Kuang, B.: Data integrity verification of the outsourced big data in the cloud environment: a survey. J. Netw. Comput. Appl. 122, 1–15 (2018)CrossRefGoogle Scholar
  15. 15.
    Chaudhari, S., Pathuri, S.K.: A comprehensive survey on public auditing for cloud storage. Int. J. Eng. Technol. 7(2.7), 565–569 (2018)CrossRefGoogle Scholar
  16. 16.
    Ateniese, G., et al.: Provable data possession at untrusted stores. In: ACM Conference on Computer and Communications Security, Alexandria, Virginia, USA, pp. 598–609 (2007)Google Scholar
  17. 17.
    Sebé, F., Domingo-Ferrer, J., Martinez-Balleste, A., Deswarte, Y., Quisquater, J.: Efficient remote data possession checking in critical information infrastructures. IEEE Trans. Knowl. Data Eng. 20(8), 1034–1038 (2008)CrossRefGoogle Scholar
  18. 18.
    Ghoubach, I.E., Abbou, R.B., Mrabti, F.: A secure and efficient remote data auditing scheme for cloud storage. J. King Saud Univ. Comput. Inf. Sci. (accepted for publication)Google Scholar
  19. 19.
    Erway, C.C., Küpçü, A., Papamanthou, C., Tamassia, R.: Dynamic provable data possession. ACM Trans. Inf. Syst. Secur. 17(4), 15 (2015)CrossRefGoogle Scholar
  20. 20.
    Ren, Z., Wang, L., Wang, Q., Xu, M.: Dynamic proofs of retrievability for coded cloud storage systems. IEEE Trans. Serv. Comput. 11(4) (2018)CrossRefGoogle Scholar
  21. 21.
    Wang, Q., Wang, C., Li, J., Ren, K., Lou, W.: Enabling public verifiability and data dynamics for storage security in cloud computing. In: Backes, M., Ning, P. (eds.) ESORICS 2009. LNCS, vol. 5789, pp. 355–370. Springer, Heidelberg (2009).  https://doi.org/10.1007/978-3-642-04444-1_22CrossRefGoogle Scholar
  22. 22.
    Hao, Z., Zhong, S., Yu, N.: A privacy-preserving remote data integrity checking protocol with data dynamics and public verifiability. IEEE Trans. Knowl. Data Eng. 23(9), 1432–1437 (2011)CrossRefGoogle Scholar
  23. 23.
    Chen, L., Zhou, S., Huang, X., Xu, L.: Data dynamics for remote data possession checking in cloud storage. Comput. Electr. Eng. J. 39(7), 2413–2424 (2013)CrossRefGoogle Scholar
  24. 24.
    Saxena, R., Dey, S.: A generic approach for integrity verification big data. Cluster Comput. 22(2), 529–540 (2018)CrossRefGoogle Scholar
  25. 25.
    Wang, C., Chow, S.M., Wang, Q., Ren, K., Lou, W.: Privacy-preserving public auditing for secure cloud storage. IEEE Trans. Comput. 62(2), 362–375 (2013)MathSciNetCrossRefGoogle Scholar
  26. 26.
    Yu, Y., Ni, J., Au, M.H., Liu, H., Wang, H., Xu, C.: Improved security of a dynamic remote data possession checking protocol for cloud storage. J. Expert Syst. Appl. 41(17), 7789–7796 (2014)CrossRefGoogle Scholar
  27. 27.
    Liu, Z., Liao, Y., Yang, X., He, Y., Zhao, K.: Identity-based remote data integrity checking of cloud storage from lattices. In: International Conference on Big Data Computing and Application, Chengdu, China (2017)Google Scholar
  28. 28.
    Wang, H.: Identity-based distributed provable data possession in multicloud storage. IEEE Trans. Serv. Comput. 8(2), 328–340 (2014)CrossRefGoogle Scholar
  29. 29.
    Yu, Y., et al.: Identity-based remote data integrity checking with perfect data privacy preserving for cloud storage. IEEE Trans. Inf. Forensics Secur. 12(4), 767–778 (2017)CrossRefGoogle Scholar
  30. 30.
    Curtmola, R., Khan, O., Burns, R., Ateneise, G.: MR-PDP: multiple-replica provable data possession. In: International Conference on Distributed Computing Systems, Beijing, China (2008)Google Scholar
  31. 31.
    Zhu, Y., Hu, H., Ahn, G., Yu, M.: Cooperative provable data possession for integrity verification in multicloud storage. IEEE Trans. Parallel Distrib. Syst. 23(12), 2231–2244 (2012)CrossRefGoogle Scholar
  32. 32.
    Wei, J., Liu, J., Zhang, Ru., Niu, X.: Efficient dynamic replicated data possession checking in distributed cloud storage systems. Int. J. Distrib. Sens. Netw. 12(1) (2016)CrossRefGoogle Scholar
  33. 33.
    Nayak, S.K., Tripathy, S.: SEPDP: secure and efficient privacy preserving provable data possession in cloud storage. IEEE Trans. Serv. Comput. 1–13 (2018)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringUniversity College of Engineering TindivanamTindivanamIndia
  2. 2.Department of Computer Science and EngineeringJerusalem College of EngineeringChennaiIndia

Personalised recommendations