Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/24044
Title: Non-cooperative 802.11 MAC layer fingerprinting and tracking of mobile devices
Authors: ROBYNS, Pieter 
BONNE, Bram 
QUAX, Peter 
LAMOTTE, Wim 
Issue Date: 2017
Source: Security and Communication Networks, 2017, p. 1-21 (Art N° UNSP 6235484)
Abstract: We present two novel noncooperative MAC layer fingerprinting and tracking techniques for Wi-Fi (802.11) enabled mobile devices. Our first technique demonstrates how a per-bit entropy analysis of a single captured frame allows an adversary to construct a fingerprint of the transmitter that is 80.0 to 67.6 percent unique for 50 to 100 observed devices and 33.0 to 15.1 percent unique for 1,000 to 10,000 observed devices. We show how existing mitigation strategies such as MAC address randomization can be circumvented using only this fingerprint and temporal information. Our second technique leverages peer-to-peer 802.11u Generic Advertisement Service (GAS) requests and 802.11e Block Acknowledgement (BA) requests to instigate transmissions on demand from devices that support these protocols. We validate these techniques using two datasets, one of which was recorded at a music festival containing 28,048 unique devices and the other at our research lab containing 138 unique devices. Finally, we discuss a number of countermeasures that can be put in place by mobile device vendors in order to prevent noncooperative tracking through the discussed techniques.
Keywords: wireless security; injection attack; frame aggregation
Document URI: http://hdl.handle.net/1942/24044
Link to publication/dataset: https://www.hindawi.com/journals/scn/2017/6235484/
ISSN: 1939-0114
e-ISSN: 1939-0122
DOI: 10.1155/2017/6235484
ISI #: 000403019100001
Rights: Copyright © 2017 Pieter Robyns et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Category: A1
Type: Journal Contribution
Validations: ecoom 2018
Appears in Collections:Research publications

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