Searchable encryption(SE) allows users to efficiently retrieve data over encrypted cloud data, but most existing SE schemes only support exact keyword search, resulting in false results due to minor typos or format inconsistencies of queried keywords. The fuzzy keyword search can avoid this limitation, but still incurs low search accuracy and efficiency. Besides, most of fuzzy keyword search schemes do not consider malicious cloud servers which may execute a fraction of search operations or forge some results due to various interest incentives such as saving computation or storage resources. To solve these problems, we propose an efficient and Verifiable Ranked Fuzzy Multi-keyword Search scheme, called VRFMS. VRFMS uses locality-sensitive hashing and bloom filter to implement fuzzy keyword search, and employs Term Frequency-Inverse Document Frequency(TF-IDF) to sort the relevant results. Aiming to further improve the search accuracy, we design an improved bi-gram keyword transformation method. Furthermore, the homomorphic MAC technique and a random challenge technique are utilized to verify the correctness and completeness of returned results, respectively. Formal security analysis and empirical experiments demonstrate that VRFMS is secure and efficient in practical applications, respectively.

中文翻译：

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VRFMS：加密数据上的可验证排名模糊多关键字搜索


可搜索加密（SE）允许用户通过加密的云数据高效地检索数据，但现有的大多数SE方案仅支持精确的关键字搜索，从而导致由于查询关键字的轻微拼写错误或格式不一致而导致错误结果。模糊关键词搜索可以避免这种限制，但搜索精度和效率仍然较低。此外，大多数模糊关键词搜索方案没有考虑恶意云服务器，这些云服务器可能会由于各种利益激励（例如节省计算或存储资源）而执行部分搜索操作或伪造一些结果。为了解决这些问题，我们提出了一种高效且可验证的排名模糊多关键字搜索方案，称为 VRFMS。 VRFMS采用局部敏感哈希和布隆过滤器实现模糊关键词搜索，并采用词频-逆文档频率（TF-IDF）对相关结果进行排序。为了进一步提高搜索精度，我们设计了一种改进的二元关键词变换方法。此外，还分别利用同态MAC技术和随机挑战技术来验证返回结果的正确性和完整性。形式安全分析和实证实验分别证明了VRFMS在实际应用中是安全和高效的。