DPPS: A novel dual privacy-preserving scheme for enhancing query privacy in continuous location-based services  

作　　者：Long LI Jianbo HUANG Liang CHANG Jian WENG Jia CHEN Jingjing LI 

机构地区：[1]College of Cyber Security,Jinan University,Guangzhou 510632,China [2]Guangxi Key Laboratory of Trusted Software,Guilin University of Electronic Technology,Guilin 541004,China [3]Department of Computer Applications,Guilin University of Technology at Nanning,Nanning 530000,China

出　　处：《Frontiers of Computer Science》2023年第5期197-205,共9页中国计算机科学前沿（英文版）

基　　金：supported by the National Natural Science Foundation of China(Grant No.62172350);the Fundamental Research Funds for the Central Universities(No.21621028);the Innovation Project of GUET Graduate Education(No.2022YCXS083).

摘　　要：Since smartphones embedded with positioning systems and digital maps are widely used,location-based services(LBSs)are rapidly growing in popularity and providing unprecedented convenience in people’s daily lives;however,they also cause great concern about privacy leakage.In particular,location queries can be used to infer users’sensitive private information,such as home addresses,places of work and appointment locations.Hence,many schemes providing query anonymity have been proposed,but they typically ignore the fact that an adversary can infer real locations from the correlations between consecutive locations in a continuous LBS.To address this challenge,a novel dual privacy-preserving scheme(DPPS)is proposed that includes two privacy protection mechanisms.First,to prevent privacy disclosure caused by correlations between locations,a correlation model is proposed based on a hidden Markov model(HMM)to simulate users’mobility and the adversary’s prediction probability.Second,to provide query probability anonymity of each single location,an advanced k-anonymity algorithm is proposed to construct cloaking regions,in which realistic and indistinguishable dummy locations are generated.To validate the effectiveness and efficiency of DPPS,theoretical analysis and experimental verification are further performed on a real-life dataset published by Microsoft,i.e.,GeoLife dataset.

关 键 词：location-based services PRIVACY-PRESERVING hidden Markov model K-ANONYMITY query probability 

分 类 号：TN9[电子电信—信息与通信工程]