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Title:
PEKSrand: Providing Predicate Privacy in Public-key Encryption with Keyword Search
Authors: Benwen Zhu, Bo Zhu, Kui Ren
Abstract:Recently, Shen, Shi, and Waters introduced the notion of predicate privacy, i.e., the property that t(x) reveals no information about the encoded predicate p, and proposed a scheme that achieves predicate privacy in the symmetric-key settings. In this paper, we propose two schemes. In the first scheme, we extend PEKS to support predicate privacy based on the idea of randomization. To the best of our knowledge, this is the first work that ensures predicate privacy in the publickey settings without requiring interactions between the receiver and potential senders, the size of which may be very large. Moreover, we identify a new type of attacks against PEKS, i.e., statistical guessing attacks. Accordingly, we introduce a new notion called statistics privacy, i.e., the property that predicate privacy is preserved even when the statistical distribution of keywords is known, and propose a scheme that makes a tradeoff between statistics privacy and storage efficiency (of the delegate). According to our analysis and experimental results, compared to PEKS, both of our schemes introduce reasonable additional communication and computation overheads and can be smoothly deployed in existing systems.
ePrint: https://eprint.iacr.org/2010/466
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