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Substring Position Search over Encrypted Cloud Data Supporting Efficient Multi-User Setup ?

机译:支持有效的多用户设置的加密云数据上的子字符串位置搜索?

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Existing Searchable Encryption (SE) solutions are able to handle simple Boolean search queries, such as single or multi-keyword queries, but cannot handle substring search queries over encrypted data that also involve identifying the position of the substring within the document. These types of queries are relevant in areas such as searching DNA data. In this paper, we propose a tree-based Substring Position Searchable Symmetric Encryption (SSP-SSE) to overcome the existing gap. Our solution efficiently finds occurrences of a given substring over encrypted cloud data. Specifically, our construction uses the position heap tree data structure and achieves asymptotic efficiency comparable to that of an unencrypted position heap tree. Our encryption takes O ( k n ) time, and the resulting ciphertext is of size O ( k n ) , where k is a security parameter and n is the size of stored data. The search takes O ( m 2 + o c c ) time and three rounds of communication, where m is the length of the queried substring and o c c is the number of occurrences of the substring in the document collection. We prove that the proposed scheme is secure against chosen-query attacks that involve an adaptive adversary. Finally, we extend SSP-SSE to the multi-user setting where an arbitrary group of cloud users can submit substring queries to search the encrypted data.
机译:现有的可搜索加密(SE)解决方案能够处理简单的布尔搜索查询(例如单关键字查询或多关键字查询),但无法处理对加密数据的子字符串搜索查询,该查询还涉及标识子字符串在文档中的位置。这些类型的查询与DNA数据搜索等领域相关。在本文中,我们提出了一种基于树的子串位置可搜索对称加密(SSP-SSE),以克服现有差距。我们的解决方案可以有效地发现加密云数据上给定子字符串的出现。具体来说,我们的构造使用位置堆树数据结构,并实现了与未加密的位置堆树相当的渐近效率。我们的加密需要O(k n)时间,并且所得密文的大小为O(k n),其中k是安全参数,n是存储数据的大小。搜索需要O(m 2 + o c c)时间和三轮通讯,其中m是查询的子字符串的长度,而o c c是在文档集合中子字符串出现的次数。我们证明了所提出的方案对于涉及自适应对手的选择查询攻击是安全的。最后,我们将SSP-SSE扩展到多用户设置,在该设置中,任意一组云用户都可以提交子字符串查询以搜索加密的数据。

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