In the area of information retrieval, in order to improve search accuracy and reduce communication overhead, there is an increasing tendency to adopt ranked search in engines. Ranked search allows cloud servers to search for the top k most relevant documents based on the relevance score between the query keywords and the documents. Recently, with the increasing popularity of encrypted search technologies, ranked searchable encryption is proposed accordingly which focuses on solving ranked search problem over encrypted databases. However, recent studies show that some privacy protection methods commonly used in ranked searchable encryption, like order-preserving encryption (OPE), have some security problems. These problems may lead to the leakage of the relevant ranking privacy information. Meanwhile, most of the existing ranked searchable encryption schemes do not consider the problem of payment for outsourced services. In this paper, we propose a scheme called ranked searchable encryption based on differential privacy and blockchain (DPB-RSE). Specifically, we first add noise drawn from a Laplace distribution into the relevance score to disturb its value. Then we design a smart contract to verify the correctness of the results returned by the cloud server and realize payment fairness. The experiment results demonstrate that the accuracy of search results in this scheme can reach 94% in a small privacy budge.

在信息检索领域，为了提高搜索精度，减少通信开销，越来越多的引擎采用排名搜索。排名搜索允许云服务器搜索前k基于查询关键字和文档之间的相关性分数的最相关文档。近年来，随着加密搜索技术的日益普及，相应地提出了排序可搜索加密，其重点是解决加密数据库上的排序搜索问题。然而，最近的研究表明，排序可搜索加密中常用的一些隐私保护方法，如保序加密（OPE），存在一些安全问题。这些问题可能导致相关排名隐私信息的泄露。同时，现有的排名可搜索加密方案大多没有考虑外包服务的付费问题。在本文中，我们提出了一种称为基于差分隐私和区块链的排名可搜索加密（DPB-RSE）的方案。具体来说，我们首先将来自拉普拉斯分布的噪声添加到相关分数中以扰乱其值。然后我们设计了一个智能合约来验证云服务器返回结果的正确性，实现支付公平。实验结果表明，该方案在较小的隐私预算下搜索结果的准确率可以达到94%。