Stay Connected, Leave no Trace: Enhancing Security and Privacy in WiFi via Obfuscating Radiometric Fingerprints


연구 분야: Analysis



학회: Proceedings of the ACM on Measurement and Analysis of Computing Systems, Volume 4, Issue 3


초록

The intrinsic hardware imperfection of WiFi chipsets manifests itself in the transmitted signal, leading to a unique radiometric fingerprint. This fingerprint can be used as an additional means of authentication to enhance security. In fact, recent works propose practical fingerprinting solutions that can be readily implemented in commercial-off-the-shelf devices. 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-based signature can be abused to violate privacy by tracking the user device, and, as of today, users do not have any means to prevent such privacy attacks other than turning off the device. We propose RF-Veil, a radiometric fingerprinting solution that not only is robust against impersonation attacks but also protects user 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.


Author Profile
Luis Fernando Abanto-Leon

Technical University of Darmstadt Darmstadt Germany

Germany
Author Profile
Andreas Bäuml

Technical University of Darmstadt Darmstadt Germany

Germany
Author Profile
Gek Hong Sim

Technical University of Darmstadt Darmstadt Germany

Germany

📄 논문 정보

발행 연도 2020년
인용수 28
출판 국가 Germany
사이트 ACM
좋아요 수 0

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