Computer Science

Computer Science ›› 2023, Vol. 50 ›› Issue (11A): 221000036-9.doi: 10.11896/jsjkx.221000036

• Information Security • Previous Articles     Next Articles

Dummy Location Generation Algorithm Against Side Information Inference Attack

ZHANG Xuejun1, YANG Yixing1, LI Jiale1, TIAN Feng2, HUANG Haiyan1, HUANG Shan3   

  1. 1 School of Electronics and Information Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China
    2 School of Computer Science,Shaanxi Normal University,Xi'an 710062,China
    3 College of Civil Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China
  • Published:2023-11-09
  • About author:ZHANG Xuejun,born in 1977,Ph.D,professor,is a senior member of China Computer Federation.His main research interests include edge computing,differential privacy,network security,data privacy and machine learning,etc.
  • Supported by:
    National Natural Science Foundation of China(61762058,61901201),Natural Science Foundation of Gansu Pro-vince(21JR7RA282),Foundation of A Hundred Youth Talents Training Program of Lanzhou Jiaotong University,the Education Department of Gansu Province:Industrial Support Plan Project(2022CYZC-38),Fundamental Research Program of the Central Universities (GK202103090) and Natural Science Basic Research Project of Shaanxi Province(2022JM-329).

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Abstract: Aiming at the existing dummy location generation algorithm,a multiple query request attack algorithm (MQRA) is designed to test its security.In order to effectively protect user’s location privacy,a dummy location generation algorithm against side information inference attack(DLG_SIA) is proposed.It comprehensively considers the side information such as query probability,time distribution,location semantics and physical dispersion to generate an effective dummy location set to resist probability distribution attacks,location semantics attacks and location homogeneity attacks,and avoid attackers filtering dummy locations with side information.When the user requests for the first time,the DLG_SIA algorithm first uses the location entropy and time entropy to select the location points with similar query probability at the current request time to generate a dummy location set,and then uses the adjusted cosine similarity to generate the location points that meet the semantic differences.Next,distance entropy is used to ensure that the selected location points have a larger anonymous range,and the best dummy location set of the current request location is cached.Security analysis and simulation results show that MQRA algorithm can identify the real location of users in the dummy location set with high probability.Compared with the existing dummy location generation algorithm,DLG_SIA algorithm can effectively resist the side information inference attack and protect the user’s location privacy.

Key words: Location-based service, Query probability, Location semantics, Time distribution, Physical dispersion

CLC Number: 

  • TP309
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