Abstract

Secure semantic searching provides privacy-preserving information retrieval for arbitrary queries semantically related to keywords. However, current verification mechanisms cannot verify the correctness of search results for semantically related queries in mutual distrust scenarios. Moreover, most secure semantic searching schemes still perform exact matching on ciphertext after query expansion, then directly accumulate the weights of the matched keywords as similarity measurements to rank the documents, resulting in the search results with unsatisfied ranking. In this paper, we propose a secure heuristic semantic searching scheme, in which a privacy-preserving word nonlinear matching (PPWNM) method is developed, and a blockchain-based verification is designed to obtain trustworthy search results with high retrieval accuracy. Specifically, we describe several retrieval heuristics and formulate them as a word nonlinear matching problem, then transform it to the PPWNM problem for calculating the similarity measurement between the query and document so that the highly accurate ranked results can be obtained. Also we design a blockchain-based verification mechanism in which the blockchain nodes utilize the proofs generated during the matching process to verify the correctness of the search results and reach a consensus to ensure the trustworthy results and fair payment between the participants in a mutual distrust model. Our security analysis and experimental results show that the proposed scheme is secure and has higher accuracy compared with the existing other schemes.

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