Security in Emerging Wireless Communication and Networking Systems. First International ICST Workshop, SEWCN 2009, Athens, Greece, September 14, 2009, Revised Selected Papers

Research Article

RSSI-Based User Centric Anonymization for Location Privacy in Vehicular Networks

Download127 downloads
  • @INPROCEEDINGS{10.1007/978-3-642-11526-4_4,
        author={Yu-Chih Wei and Yi-Ming Chen and Hwai-Ling Shan},
        title={RSSI-Based User Centric Anonymization for Location Privacy in Vehicular Networks},
        proceedings={Security in Emerging Wireless Communication and Networking Systems. First International ICST Workshop, SEWCN 2009, Athens, Greece, September 14, 2009, Revised Selected Papers},
        proceedings_a={SEWCN},
        year={2012},
        month={5},
        keywords={VANET Location Privacy Tracking Anonymity},
        doi={10.1007/978-3-642-11526-4_4}
    }
    
  • Yu-Chih Wei
    Yi-Ming Chen
    Hwai-Ling Shan
    Year: 2012
    RSSI-Based User Centric Anonymization for Location Privacy in Vehicular Networks
    SEWCN
    Springer
    DOI: 10.1007/978-3-642-11526-4_4
Yu-Chih Wei,*, Yi-Ming Chen1,*, Hwai-Ling Shan2,*
  • 1: National Central University
  • 2: Information & Communication Security Lab., Chunghwa Telecommunication Labs
*Contact email: 964403007@cc.ncu.edu.tw, cym@cc.ncu.edu.tw, shanhl@cht.com.tw

Abstract

In Vehicular Networks, for enhancing driving safety as well as supporting other applications, vehicles periodically broadcast safety messages with their precise position information to neighbors. However, these broadcast messages make it easy to track specific vehicles and will likely lead to compromise of personal privacy. Unfortunately, current location privacy enhancement methodologies in VANET, including Pseudonymization, K-anonymity, Random silent period, Mix-zones and path confusion, all suffer some shortcomings. In this paper, we propose a RSSI (Received Signal Strength Indicator)-based user centric anonymization model, which can significantly enhance the location privacy and at the same time ensure traffic safety. Simulations are performed to show the advantages of the proposed method. In comparison with traditional random silent period method, our method can increase at least 47% of anonymity in both simple and correlation tracking.