Location Privacy-Preserving Method Based on Degree of Semantic Distribution Similarity

作     者：Rui Liu Kaizhong Zuo Yonglu Wang Jun Zhao 

作者机构：College of Computer and InformationAnhui Normal UniversityWuhu 241002AnhuiChina Anhui Provincial Key Laboratory of Network and Information SecurityAnhui Normal UniversityWuhu 241002AnhuiChina 

出 版 物：《国际计算机前沿大会会议论文集》 (International Conference of Pioneering Computer Scientists, Engineers and Educators（ICPCSEE）)

年 卷 期：2020年第1期

页      面：118-129页

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

基　　金：This paper was supported by the National Natural Science Foundation of China under Grant No.61672039 and 61370050 the Key Program of Universities Natural Science Research of the Anhui Provincial Department of Education under Grant No.KJ2019A1164 

主　　题：Location-based services Road network Semantic location Privacy-preserving 

摘      要：While enjoying the convenience brought by location-based services,mobile users also face the risk of leakage of location ***,it is necessary to protect location *** existing privacy-preserving methods are based on K-anonymous and L-segment diversity to construct an anonymous set,but lack consideration of the distribution of semantic location on the road ***,the number of various semantic location types in the anonymous set varies greatly,which leads to semantic inference attack and privacy *** solve this problem,a privacy-preserving method is proposed based on degree of semantic distribution similarity on the road segment,ensuring the privacy of the anonymous ***,the feasibility and effectiveness of the method are proved by extensive experiments evaluations based on dataset of real road network.