文献类型：期刊文献

英文题名：Constructing dummy query sequences to protect location privacy and query privacy in location-based services

作者：Wu, Zongda[1];Li, Guiling[2,3];Shen, Shigen[1];Lian, Xinze[4];Chen, Enhong[5];Xu, Guandong[6]

机构：[1]Shaoxing Univ, Dept Comp Sci & Engn, Shaoxing, Zhejiang, Peoples R China;[2]China Univ Geosci, Sch Comp Sci, Wuhan, Peoples R China;[3]China Univ Geosci, Hubei Key Lab Intelligent Geoinformat Proc, Wuhan, Peoples R China;[4]Wenzhou Univ, Oujiang Coll, Wenzhou, Zhejiang, Peoples R China;[5]Univ Sci & Technol China, Sch Comp Sci & Technol, Hefei, Peoples R China;[6]Univ Technol Sydney, Fac Engn & IT, Ultimo, Australia

年份：2021

卷号：24

期号：1

起止页码：25

外文期刊名：WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS

收录：SCI-EXPANDED(收录号：WOS:000545941300002)、、EI(收录号：20202808922625)、Scopus(收录号：2-s2.0-85087655391)、WOS

基金：The work is supported by the Zhejiang Provincial Natural Science Foundation of China (Nos. LZ18F020001 and LY19F020018), the National Natural Science Foundation of China (Nos. 61762055, 61702468 and 61962029), the National Social Science Foundation of China (No. 19BTQ056) and Open Research Project of The Hubei Key Laboratory of Intelligent Geo-Information Processing (No. KLIGIP-2018B03).

语种：英文

外文关键词：Location-based service; Location privacy; Query privacy; Privacy protection

外文摘要：Location-based services (LBS) have become an important part of people's daily life. However, while providing great convenience for mobile users, LBS result in a serious problem on personal privacy, i.e., location privacy and query privacy. However, existing privacy methods for LBS generally take into consideration only location privacy or query privacy, without considering the problem of protecting both of them simultaneously. In this paper, we propose to construct a group of dummy query sequences, to cover up the query locations and query attributes of mobile users and thus protect users' privacy in LBS. First, we present a client-based framework for user privacy protection in LBS, which requires not only no change to the existing LBS algorithm on the server-side, but also no compromise to the accuracy of a LBS query. Second, based on the framework, we introduce a privacy model to formulate the constraints that ideal dummy query sequences should satisfy: (1) the similarity of feature distribution, which measures the effectiveness of the dummy query sequences to hide a true user query sequence; and (2) the exposure degree of user privacy, which measures the effectiveness of the dummy query sequences to cover up the location privacy and query privacy of a mobile user. Finally, we present an implementation algorithm to well meet the privacy model. Besides, both theoretical analysis and experimental evaluation demonstrate the effectiveness of our proposed approach, which show that the location privacy and attribute privacy behind LBS queries can be effectively protected by the dummy queries generated by our approach.