802.11 User Anonymization

Privacy issues have been a serious concern for 802.11 Wireless LAN users. As demonstrated by Pang et al. and Xu et al., applying pseudonym techniques does not completely protect users' privacy. In particular, users' identities can be disclosed through implicit identifiers such as the IP addresses and port numbers users often access. In this paper, we study how to improve user anonymity even if implicit identifiers based identification is applied. The basic idea of our approach is to artificially generate bogus data and inject them into original traffic, and thus users' behavior patterns are disturbed. Specifically, we propose eight different methods to generate bogus data, where each of them applies different algorithms and metrics to generate bogus packets. Our simulation results with SIGCOMM 2004 wireless trace demonstrate that our anonymization methods can decrease user identification rates, and hence improve user anonymity.