802.11 user fingerprinting

  • Authors:
  • Jeffrey Pang;Ben Greenstein;Ramakrishna Gummadi;Srinivasan Seshan;David Wetherall

  • Affiliations:
  • Carnegie Mellon University;Intel Research Seattle;University of Southern California;Carnegie Mellon University;University of Washington

  • Venue:
  • Proceedings of the 13th annual ACM international conference on Mobile computing and networking
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

The ubiquity of 802.11 devices and networks enables anyone to track our every move with alarming ease. Each 802.11 device transmits a globally unique and persistent MAC address and thus is trivially identifiable. In response, recent research has proposed replacing such identifiers with pseudonyms (i.e., temporary, unlinkable names). In this paper, we demonstrate that pseudonyms are insufficient to prevent tracking of 802.11 devices because implicit identifiers, or identifying characteristics of 802.11 traffic, can identify many users with high accuracy. For example, even without unique names and addresses, we estimate that an adversary can identify 64% of users with 90% accuracy when they spend a day at a busy hot spot. We present an automated procedure based on four previously unrecognized implicit identifiers that can identify users in three real 802.11 traces even when pseudonyms and encryption are employed. We find that the majority of users can be identified using our techniques, but our ability to identify users is not uniform; some users are not easily identifiable. Nonetheless, we show that even a single implicit identifier is sufficient to distinguish many users. Therefore, we argue that design considerations beyond eliminating explicit identifiers (i.e., unique names and addresses), must be addressed in order to prevent user tracking in wireless networks.