Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (7): 164-171.doi: 10.11896/jsjkx.200800069

• Database & Big Data & Data Science • Previous Articles     Next Articles

Dummy Location Generation Method Based on User Preference and Location Distribution

WANG Hui, ZHU Guo-yu, SHEN Zi-hao, LIU Kun, LIU Pei-qian   

  1. College of Computer Science and Technology,Henan Polytechnic University,Jiaozuo,Henan 454003,China
  • Received:2020-08-11 Revised:2020-11-12 Online:2021-07-15 Published:2021-07-02
  • About author:WANG Hui,born in 1975,Ph.D,professor,Ph.D supervisor,is a member of China Computer Federation.His main research interests include mobile Internet privacy protection,network information security,information system development and simulation and so on.(204932059@qq.com)
    SHEN Zi-hao,born in 1980,Ph.D,lecturer,is a member of China Computer Federation.His main research interests include network and information security,information simulation,intelligent information processing and so on.
  • Supported by:
    National Natural Science Foundation of China(61300216).

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Abstract: The traditional dummy location generation algorithm based on k-anonymity mechanism has low rationality and is vulnerable to attack by attackers using side information.Aiming at solving this problem,the SPDGM algorithm is proposed.Firstly,this algorithm defines the semantic weighted digraph to describe the time distribution and semantic transfer relationship of semantics.Secondly,for the sake of solving the problem of weak resistance caused by only considering the historical probability of location,this algorithm defines the location credibility,which considers the historical probability of location and the evaluation information of the public.Thirdly,in order to avoid the dense distribution of dummy location,the dispersion degree is defined to control the distribution of dummy location.Finally,this algorithm generates an anonymous set whose semantics safe and distribution sparsely.The experimental results show that the SPDGM algorithm has lower recognition rate and higher privacy protection strength under the semantic attack,and the running time of the algorithm considering semantic attack is lower.Therefore,SPDGM algorithm is feasibility and practicability.

Key words: Distribution metric, Dummy location, Location privacy-perserving, Semantic transfer, User preference

CLC Number: 

  • TP309
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