Abstract
Searchable Symmetric Encryption (SSE) which enables keyword searches on encrypted data, has drawn a lot of research attention in recent years. However, many SSE schemes do not support privacy-preserving relevance ranking which is a necessary feature for users to quickly locate the needed documents in a large number of retrieved documents. In this paper, we proposed two Privacy-Preserving Relevance Ranking (PPRR) schemes based on RSA encryption and ElGamal encryption. The proposed PPRR schemes preserve rank privacy and reduce storage cost at server side. Furthermore, we integrate PPRR with current multi-keyword SSE algorithm to achieve multi-keyword ranked search on encrypted data. Computation complexity, storage complexity and security of composite schemes are verified with an experiment on real-world dataset.
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This work was supported by National Science and Technology Major Project (No. 2016ZX05047003).
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Shen, P., Chen, C., Zhu, X. (2018). Privacy-Preserving Relevance Ranking Scheme and Its Application in Multi-keyword Searchable Encryption. In: Lin, X., Ghorbani, A., Ren, K., Zhu, S., Zhang, A. (eds) Security and Privacy in Communication Networks. SecureComm 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 238. Springer, Cham. https://doi.org/10.1007/978-3-319-78813-5_7
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DOI: https://doi.org/10.1007/978-3-319-78813-5_7
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