Abstract
With the rapid development of the IoT and the mobile applications, users are tending to outsource the data to the cloud servers. Thus, the encrypted data search on the cloud is very important. Now there are a lot existed keyword search schemes in which the relationship between the size of the file set and the search time is linear. In order to solve this problem, we propose a semantic retrieval framework for central word expansion based on two-level index. In this paper, we have taken a new approach for index construction - the two-level index to ensure that the retrieval time is not affected by the file size. In order to better meet the semantic requirements of user queries, we introduced the central word expansion technology to further improve the accuracy of the search. The main idea of central keyword extension semantic search (CKESS) based on two-level index is that match the expanded central keyword with index firstly, then compute the similarity between the query and the index under the first matching result, and finally return the result with the highest similarity. Our proposed solution meets the privacy protection requirements under two different threat models. Through the experiment of the real data set, we prove that our scheme is efficient, accurate and secure.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Goh, E.J.: Secure indexes. Submission (2003)
Sun, W., Wang, B., Cao, N., Li, M., Lou, W., et al.: Verifiable privacy-preserving multi-keyword text search in the cloud supporting similarity-based ranking. IEEE Trans. Parallel Distrib. Syst. 25(11), 3025–3035 (2014)
Katz, J., Sahai, A., Waters, B.: Predicate encryption supporting disjunctions, polynomial equations, and inner products. J. Cryptol. 26(2), 192–224 (2013)
Fu, Z., Sun, X., Liu, Q., Zhou, L., Shu, J.: Achieving efficient cloud search services: multi-keyword ranked search over encrypted cloud data supporting parallel computing. IEICE Trans. Commun. 98(1), 190–200 (2015)
Cao, N., Wang, C., Li, M.: Privacy-preserving multi-keyword ranked search over encrypted cloud data. IEEE Trans. Parallel Distrib. Syst. 25(1), 222–233 (2014)
Har-Peled, S., Indyk, P., Motwani, R.: Approximate nearest neighbor: towards removing the curse of dimensionality. In: ACM Symposium on Theory of Computing, pp. 604–613 (1998)
Bloom, B.H.: Space/time trade-offs in hash coding with allowable errors. Commun. ACM 13(7), 422–426 (1970)
Miller, G.A., Beckwith, R., Fellbaum, C., Gross, D., Miller, K.J.: Introduction to WordNet: an on-line lexical database*. Int. J. Lexicogr. 3(4), 235–244 (1990)
Fu, Z., Ren, K., Shu, J., Sun, X., Huang, F.: Enabling personalized search over encrypted outsourced data with efficiency improvement. IEEE Trans. Parallel Distrib. Syst. 27(9), 2546–2559 (2016)
Lin, D.: An information-theoretic definition of similarity. In: Fifteenth International Conference on Machine Learning. Morgan Kaufmann Publishers Inc., pp. 296–304 (1998)
Wong, W.K., Cheung, D.W., Kao, B., Mamoulis, N.: Secure kNN computation on encrypted databases. In: ACM SIGMOD International Conference on Management of Data. ACM, pp. 139–152 (2009)
Yang, J., Liu, Z., Li, J., Jia, C., Cui, B.: Multi-key searchable encryption without random Oracle. In: International Conference on Intelligent NETWORKING and Collaborative Systems. IEEE, pp. 79–84 (2015)
Chen, X., Huang, X., Li, J., et al.: New algorithms for secure outsourcing of LargeScale systems of linear equations. IEEE Trans. Inf. Forensics Secur. 10(1), 69–78 (2014)
Wang, B., Li, M., Wang, H., Li, H.: Circular range search on encrypted spatial data. In: Communications and Network Security, pp. 182–190. IEEE (2015)
Li, J., Wang, Q., Wang, C., Cao, N., Ren, K., Lou, W.: Fuzzy keyword search over encrypted data in cloud computing. In: Conference on Information Communications, pp. 441–445. IEEE Press (2010)
Chuah, M., Hu, W.: Privacy-aware BedTree based solution for fuzzy multi-keyword search over encrypted data. In: International Conference on Distributed Computing Systems Workshops. IEEE Computer Society, pp. 273–281 (2011)
Kuzu, M., Islam, M.S., Kantarcioglu, M.: Efficient similarity search over encrypted data. In: IEEE International Conference on Data Engineering, pp. 1156–1167. IEEE (2012)
Wang, J., Yu, X., Zhao, M.: Privacy-preserving ranked multi-keyword fuzzy search on cloud encrypted data supporting range query. Arab. J. Sci. Eng. 40(8), 2375–2388 (2015)
Fu, Z., Wu, X., Guan, C., Sun, X., Ren, K.: Toward efficient multi-keyword fuzzy search over encrypted outsourced data with accuracy improvement. IEEE Trans. Inf. Forensics Security 11(12), 2706–2716 (2017)
Sun, X., Zhu, Y., Xia, Z., et al.: Secure keyword-based ranked semantic search over encrypted cloud data. In: The International Conference on Multimedia, Computer Graphics and Broadcasting, pp. 271–283 (2013)
Acknowledgment
This work is supported by the NSFC (61772283, 61672294, U1536206, 61502242, U1405254, 61602253), BK20150925, R2017L05, PAPD fund, Project funded by China Postdoctoral Science Foundation, Major Program of the National Social Science Fund of China (17ZDA092), Qing Lan Project, and Meteorology Soft Sciences Project.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Xia, L., Fu, Z. (2018). Secure Semantic Search Based on Two-Level Index Over Encrypted Cloud. In: Au, M., et al. Network and System Security. NSS 2018. Lecture Notes in Computer Science(), vol 11058. Springer, Cham. https://doi.org/10.1007/978-3-030-02744-5_11
Download citation
DOI: https://doi.org/10.1007/978-3-030-02744-5_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-02743-8
Online ISBN: 978-3-030-02744-5
eBook Packages: Computer ScienceComputer Science (R0)