2nd International ICST Conference on Security and Privacy in Comunication Networks

Research Article

Enhancing Privacy Preservation of Anonymous Location Sampling Techniques in Traffic Monitoring Systems

  • @INPROCEEDINGS{10.1109/SECCOMW.2006.359553,
        author={Baik  Hoh and Marco Gruteser and Hui  Xiong and Ansaf  Alrabady},
        title={Enhancing Privacy Preservation of Anonymous Location Sampling Techniques in Traffic Monitoring Systems},
        proceedings={2nd International ICST Conference on Security and Privacy in Comunication Networks},
        publisher={IEEE},
        proceedings_a={SECURECOMM},
        year={2007},
        month={5},
        keywords={},
        doi={10.1109/SECCOMW.2006.359553}
    }
    
  • Baik Hoh
    Marco Gruteser
    Hui Xiong
    Ansaf Alrabady
    Year: 2007
    Enhancing Privacy Preservation of Anonymous Location Sampling Techniques in Traffic Monitoring Systems
    SECURECOMM
    IEEE
    DOI: 10.1109/SECCOMW.2006.359553
Baik Hoh1,*, Marco Gruteser1,*, Hui Xiong2,*, Ansaf Alrabady3,*
  • 1: WINLAB, ECE Dept., Rutgers Univ.
  • 2: MSIS Dept., Rutgers Univ.
  • 3: General Motors Corporation
*Contact email: baikhoh@winlab.rutgers.edu, gruteser@winlab.rutgers.edu, hui@rbs.rutgers.edu, ansaf.alrabady@gm.com

Abstract

Automotive traffic monitoring belongs to a class of applications that collect aggregate statistics from the location traces of a large number of users. A widely-accepted belief is that anonymization of individual records can address the privacy problem which such aggregate statistics might pose. However, in this paper, we show that data mining techniques, such as clustering, can reconstruct private information from such anonymous traces. To meet this new challenge, we propose enhanced privacy-preserving algorithm to control the release of location traces near origins/destinations and evaluate it using real-world GPS location traces