Stay Connected, Leave no Trace
Enhancing Security and Privacy in WiFi via Obfuscating Radiometric Fingerprints
Luis F. Abanto-Leon (Technische Universität Darmstadt)
Andreas Bäuml (Technische Universität Darmstadt)
Gek Hong Allyson Sim (Technische Universität Darmstadt)
Matthias Hollick (Technische Universität Darmstadt)
A. Asadi (Communication and Sensing Lab (WiSe) and SEEMOO)
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Abstract
The intrinsic hardware imperfection of WiFi chipsets manifests itself in the transmitted signal, leading to a unique radiometric (radio frequency) fingerprint. This fingerprint can be used as an additional means of authentication to enhance security. In this paper, we prove analytically and experimentally that these solutions are highly vulnerable to impersonation attacks. We also demonstrate that such a unique device-specific signature can be abused to track devices, thus violating privacy. We propose RF-Veil, a radiometric fingerprinting solution that is not only robust against impersonation attacks but also effective in protecting privacy by obfuscating the radiometric fingerprint of the transmitter for non-legitimate receivers. Specifically, we introduce a randomized pattern of phase errors to the transmitted signal such that only the intended receiver can extract the original fingerprint of the transmitter. In a series of experiments and analyses, we expose the vulnerability of adopting naive randomization to statistical attacks and introduce countermeasures. Finally, we show the efficacy of RF-Veil experimentally in protecting user privacy and enhancing security. More importantly, our proposed solution allows communicating with other devices, which do not employ RF-Veil.
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