Author : Sana Shaikh 1
Date of Publication :22nd February 2018
Abstract: Today most organizations prefer to outsource their data on cloud. The outsourced documents and files should be encrypted because of the protection and secrecy worries of their proprietor. As a large amount of data from various clients is getting accumulated on cloud, this raises the issue of security and privacy to its proprietors. Data being large, quick efficient and authorized search is a challenge. An efficient multi-keyword ranked search scheme is proposed in this paper that is able to address the aforementioned problems. Bloom filters are used to enhance search duration. Relevance scoring technique is used to generate ranking results in view of the top-k precision. Inside of this framework, we implemented the blind storage technique to cover access pattern of the search user. Till now the search authorization problem was not considered, that is the cloud server only has to return the search results to authorized users. In this paper, we propose an authorized and ranked multi-keyword search scheme over encrypted cloud data. Identity Based-authentication is used for authentication with AES for encryption. As a result, information leakage can be eliminated and data security is ensured. Security and performance analysis show that the proposed scheme can achieve much improved efficiency in terms of accuracy, search time and security compared with the search algorithm used in EMRS i.e Efficient Multi-keyword Rank Search scheme.
Reference :
-
- C. Wang, N. Cao, J. Li, K. Ren, and W. Lou, „„Secure ranked keyword search over encrypted cloud data,‟‟ in Proc. IEEE 30th Int. Conf. Distrib. Comput. Syst. (ICDCS). 2010 .pp.253-262
- J. Yu, P. Lu, Y. Zhu, G. Xue, and M. Li, „„Toward secure multi keyword top-k retrieval over encrypted cloud data, ‟‟IEEE Trans. Dependable Secure Computer., vol. 10, no. 4, pp. 239–250, Jul./Aug. 2013
- Zhihua Xia, Li Chen, Xingming Sun, and Jin Wang “An Efficient and Privacy-Preserving Semantic Multi-Keyword Ranked Search over Encrypted Cloud Data” International Journal of Security and Its Applications Vol.8, No.2 (2014), pp.323-332
- W. K. Wong, D. W. Cheung, B. Kao, and N. Mamoulis, ``Secure kNN computation on encrypted databases,'' in Proc. ACM SIGMOD Int. Conf. Manage Data, 2009, pp. 139-152.
- W. Sun, et al., ``Privacy-preserving multi-keyword text search in the cloud supporting similarity-based ranking,'' in Proc. 8th ACM SIGSAC Symp. Information, Computer. Communication .Security., 2013, pp. 71-82.