An Effective and Fine Grained Big Data access Control Scheme with Protection Policy
Keywords:
CP-ABE, Big data, Decryption, Secret-sharingAbstract
In order to control the access of the huge amount of big data becomes a very challenging issue, especially when big-data are stored in the cloud. Cipher text- policy attribute-based encryption (CP-ABE) is a promising encryption technique that enables end-users to encrypt their data under the access policies defined over some attributes of data consumers and only allows data consumers whose attributes satisfy the access policies to decrypt the data. In CP-ABE, the access policy is attached to the cipher text in plaintext form, which may also leak some private information about end-users. Existing methods only partially hide the attribute values in the access policies, while the attribute names are still unprotected. In this paper, we propose an efficient and fine-grained big data access control scheme with privacy-preserving policy. Specifically, we hide the whole attribute (rather than only its values) in the access policies. To assist data decryption, we also design a novel attribute bloom filter to evaluate whether an attribute is in the access policy and locate the exact position in the access policy, if it is in the access policy. Security analysis and performance evaluation show that our scheme can preserve the privacy from any linear secret-sharing schemes access policy without employing much over head.
References
B. Grobauer, T. Walloschek, and E. Stocker, “Understanding cloud computing vulnerabilities, ”IEEE Security and Privacy, Vol.9, No. 2, 2011, pp. 50-57.
D. Boru, D. Kliazovich, F. Granelli, P. Bouvry, and A. Y. Zomaya,“Energy-efficient data replication in cloud computing datacenters,” In IEEE Globecom Workshops, 2013, pp. 446-451.
K. Bilal, M. Manzano, S. U. Khan, E. Calle, K. Li, and A.Zomaya, “On the characterization of the structural robustness of data center networks,”IEEE Transactions on Cloud Computing, Vol. 1, No. 1, 2013, pp. 64-77.
K. Bilal, S. U. Khan, L. Zhang, H. Li, K. Hayat, S. A. Madani,N. Min-Allah, L. Wang, D. Chen, M. Iqbal, C. Z. Xu, and A. Y.Zomaya, “Quantitative comparisons of the state of the art datacenter architectures,” Concurrency and Computation: Practice and Experience, Vol. 25, No. 12, 2013, pp. 1771-1783.
M. Hogan, F. Liu, A.Sokol, and J. Tong, “NIST cloud computing standards roadmap,” NIST Special Publication, July 2011.
W. A. Jansen, “Cloud hooks: Security and privacy issues in cloud computing, ”In 44th Hawaii IEEE International Conference on System Sciences (HICSS), 2011, pp. 1-10.
W. K. Hale, “Frequency assignment: Theory and applications, ”Proceedings of the IEEE, Vol. 68, No. 12, 1980, pp. 1497-1514.[7] K. Hashizume, D. G. Rosado, E. Fernandez-Medina, and E. B. Fernandez, “An analysis of security issues for cloud computing,” Journal of Internet Services and Applications, Vol. 4, No. 1,2013, pp. 1-13.
Y. Deswarte, L. Blain, and J-C. Fabre, “Intrusion tolerance in distributed computing systems,” In Proceedings of IEEE Computer Society Symposium on Research in Security and Privacy, Oakland CA, pp. 110-121, 1991.
