计算机科学
加密
范围查询(数据库)
云计算
基于位置的服务
明文
服务器
外包
计算机安全
数据挖掘
Web搜索查询
计算机网络
情报检索
搜索引擎
Web查询分类
操作系统
政治学
法学
作者
Qinlong Huang,Juan Du,Guanyu Yan,Yixian Yang,Qinglin Wei
出处
期刊:IEEE Transactions on Services Computing
[Institute of Electrical and Electronics Engineers]
日期:2022-11-01
卷期号:15 (6): 3443-3456
被引量:18
标识
DOI:10.1109/tsc.2021.3088131
摘要
With the popularization of location-based services (LBS), encryption techniques have been utilized to protect data security when outsourcing LBS to cloud. However, existing schemes only consider spatial range search or keyword search, while expressive and practical search over encrypted LBS data is still a challenging problem. In this article, we introduce PrivSTL, a privacy-preserving spatio-temporal keyword search framework over the encrypted LBS data based on attribute-based encryption, linear encryption and RSA encryption. It allows mobile users to submit LBS query with spatial range, time interval and Boolean keyword expression, and provides accurate and authorized search by matching these query conditions and also the access policy. Then we introduce an extended scheme PrivSTG, which utilizes Geohash to divide the locations into grids, and outsources an encrypted index tree to cloud servers. PrivSTG improves the service efficiency by searching only over the ciphertexts in the surrounding grids of mobile user. Finally, we analyze the security of PrivSTL against chosen-plaintext, chosen-keyword and outside keyword-guessing attacks in generic bilinear group model, and show that PrivSTL guarantees the spatio-temporal keyword profile privacy, and also protects the query privacy. The experimental results indicate that our scheme is practical and efficient for outsourced LBS.
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