云环境下基于位置堆的高效隐私保护关键字减串查询
Achieve Efficient Position-Heap-based Privacy-Preserving Substring-of-Keyword Query over Cloud
摘要：
最初用于缓解数据爆炸性增长的云计算技术，已被要求同时考虑数据隐私和用户查询功能。对称可搜索加密（SSE）是一种流行的解决方案，用于支持对云中加密数据的有效关键字查询。然而，大多数现有的SSE方案集中在精确的关键字查询上，并且当用户只记得关键字的子串时，即，关键字子串查询。本文旨在研究这个问题，提出了一个有效的和隐私保护的substring-of-keyword查询方案在云。首先，我们采用位置堆技术来设计一种新的基于树的索引，以匹配子串与相应的关键字。在基于树的索引的基础上，我们介绍了我们的关键字子串查询方案，它包含两个连续的阶段。第一阶段查询与给定子字符串匹配的关键字，第二阶段查询与人们真正感兴趣的关键字匹配的文件。此外，详细的安全性分析和实验结果表明，我们提出的方案的安全性和效率。
英文摘要：
The cloud computing technique, which was initially used to mitigate the explosive growth of data, has been required to take both data privacy and users' query functionality into consideration. Symmetric searchable encryption (SSE) is a popular solution to supporting efficient keyword queries over encrypted data in the cloud. However, most of the existing SSE schemes focus on the exact keyword query and cannot work well when the user only remembers the substring of a keyword, i.e., substring-of-keyword query. This paper aims to investigate this issue by proposing an efficient and privacy-preserving substring-of-keyword query scheme over cloud. First, we employ the position heap technique to design a novel tree-based index to match substrings with corresponding keywords. Based on the tree-based index, we introduce our substring-of-keyword query scheme, which contains two consecutive phases. The first phase queries the keywords that match a given substring, and the second phase queries the files that match a keyword in which people are really interested. In addition, detailed security analysis and experimental results demonstrate the security and efficiency of our proposed scheme.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
