计算机工程与应用2019，Vol.55Issue(5)：96-104,9.DOI:10.3778/j.issn.1002-8331.1712-0188
粒子群属性聚类的位置隐私保护
PSO Attributes Clustering for Preserving Location Privacy
摘要
Abstract
The attribute of the user can be collected by the adversary as background knowledge, as the user utilizing the continuous query in location-based service. Then with the attribute revealed along each query in the continuous request, the adversary can get the location privacy of the user with attribute correlation. In order to cope with this problem, a particle swarm optimization clustering scheme is proposed. This scheme can both accelerate the procedure of similar attributes finding and preserve the location privacy of the user. In this scheme, a central server is employed as usually assumed in the scheme of location privacy preserving. The central server performs the particle swarm optimization with the received anonymous request, and accelerates the process of choosing anonymous users with similar attributes. Then anonymous users with similar attributes will achieve the attribute anonymity and location generalization that obfuscate the correlation between each other, and then the attribute anonymity and location generalization make the adversary difficult to identify any special user with attribute correlation. At last, the experimental results verify the fact that, the particle swarm optimiza-tion scheme provides a better privacy preserving level and a faster processing speed than other similar algorithms.关键词
基于位置服务/连续查询/粒子群属性聚类/属性匿名/位置泛化/隐私保护Key words
location-based service/ continuous query/ particle swarm optimization clustering/ attribute anonymity/ location generalization/ privacy preserving分类
计算机与自动化引用本文复制引用
关巍,张磊..粒子群属性聚类的位置隐私保护[J].计算机工程与应用,2019,55(5):96-104,9.基金项目
国家自然科学基金(No.61772098,No.61772099) （No.61772098,No.61772099）
重庆市科学技术委员会基础科学与前沿技术项目(No.cstc2016jcyjA0571) （No.cstc2016jcyjA0571）
重庆邮电大学高端人才培养项目(No.BYJS2016002). （No.BYJS2016002）
