Mobile Computing, Applications, and Services. Third International Conference, MobiCASE 2011, Los Angeles, CA, USA, October 24-27, 2011. Revised Selected Papers

Research Article

Towards Location and Trajectory Privacy Protection in Participatory Sensing

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  • @INPROCEEDINGS{10.1007/978-3-642-32320-1_29,
        author={Sheng Gao and Jianfeng Ma and Weisong Shi and Guoxing Zhan},
        title={Towards Location and Trajectory Privacy Protection in Participatory Sensing},
        proceedings={Mobile Computing, Applications, and Services. Third International Conference, MobiCASE 2011, Los Angeles, CA, USA, October 24-27, 2011. Revised Selected Papers},
        proceedings_a={MOBICASE},
        year={2012},
        month={10},
        keywords={participatory sensing location privacy trajectory privacy similarity},
        doi={10.1007/978-3-642-32320-1_29}
    }
    
  • Sheng Gao
    Jianfeng Ma
    Weisong Shi
    Guoxing Zhan
    Year: 2012
    Towards Location and Trajectory Privacy Protection in Participatory Sensing
    MOBICASE
    Springer
    DOI: 10.1007/978-3-642-32320-1_29
Sheng Gao1,*, Jianfeng Ma1,*, Weisong Shi2,*, Guoxing Zhan2,*
  • 1: Xidian University
  • 2: Wayne State University
*Contact email: sgao@mail.xidian.edu.cn, jfma@mail.xidian.edu.cn, weisong@wayne.edu, gxzhan@wayne.edu

Abstract

The ubiquity of mobile devices has facilitated the prevalence of participatory sensing, whereby ordinary citizens using their private mobile devices to collect regional information and share with participators. However, such applications may endanger users’ privacy by revealing their locations and trajectories information. Most of existing solutions, which hide a user’s location information with a coarse region, are under model. Yet, they may not be applicable in some participatory sensing applications which require precise location information for high quality of service. In this paper, we present a method to protect the user’s location and trajectory privacy with high quality of service in some participatory sensing applications. Then, we utilize a new metric, called , to evaluate the method we proposed. The analysis and simulation results show that the method can protect the user’s location and trajectory privacy effectively.