How people revisit web pages: empirical findings and implications for the design of history systems
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Authentication via keystroke dynamics
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Information Retrieval
Location Privacy in Pervasive Computing
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Statistical Identification of Encrypted Web Browsing Traffic
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Wireless LAN location-sensing for security applications
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Transport layer identification of P2P traffic
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
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Remote Physical Device Fingerprinting
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PETS '09 Proceedings of the 9th International Symposium on Privacy Enhancing Technologies
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IEEE 802.11 user fingerprinting and its applications for intrusion detection
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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.