Semantic searching over encrypted data is a crucial task for secure information retrieval in public cloud. It aims to provide retrieval service to arbitrary words so that queries and search results are flexible. In existing semantic searching schemes, the verifiable searching does not be supported since it is dependent on the forecasted results from predefined keywords to verify the search results from cloud, and the queries are expanded on plaintext and the exact matching is performed by the extended semantically words with predefined keywords, which limits their accuracy. In this paper, we propose a secure verifiable semantic searching scheme. For semantic optimal matching on ciphertext, we formulate word transportation (WT) problem to calculate the minimum word transportation cost (MWTC) as the similarity between queries and documents, and propose a secure transformation to transform WT problems into random linear programming (LP) problems to obtain the encrypted MWTC. For verifiability, we explore the duality theorem of LP to design a verification mechanism using the intermediate data produced in matching process to verify the correctness of search results. Security analysis demonstrates that our scheme can guarantee verifiability and confidentiality. Experimental results on two datasets show our scheme has higher accuracy than other schemes.

中文翻译：

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公有云加密数据优化匹配的可验证语义搜索方案


对加密数据进行语义搜索是公共云中安全信息检索的一项关键任务。其目的是为任意词提供检索服务，使查询和搜索结果更加灵活。现有的语义搜索方案不支持可验证搜索，因为它依赖于预定义关键字的预测结果来验证云端的搜索结果，并且查询在明文上扩展，并通过扩展的语义词进行精确匹配使用预定义的关键字，这限制了它们的准确性。在本文中，我们提出了一种安全可验证的语义搜索方案。对于密文的语义最优匹配，我们制定了单词传输（WT）问题来计算最小单词传输成本（MWTC）作为查询和文档之间的相似度，并提出了一种安全转换，将WT问题转换为随机线性规划（LP）问题获取加密的MWTC。为了可验证性，我们探索了LP的对偶定理，设计了一种验证机制，利用匹配过程中产生的中间数据来验证搜索结果的正确性。安全分析表明我们的方案能够保证可验证性和保密性。两个数据集上的实验结果表明我们的方案比其他方案具有更高的准确性。