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

• URL: http://arxiv.org/abs/2011.12644v2
• Date: Fri, 27 Nov 2020 12:25:18 GMT
• Title: Stay Connected, Leave no Trace: Enhancing Security and Privacy in WiFi via Obfuscating Radiometric Fingerprints
• Authors: Luis F. Abanto-Leon and Andreas Baeuml and Gek Hong (Allyson) Sim and Matthias Hollick and Arash Asadi
• Abstract summary: The intrinsic hardware imperfection of WiFi chipsets manifests itself in the transmitted signal, leading to a unique radiometric fingerprint. Recent works propose practical fingerprinting solutions that can be readily implemented in commercial-off-the-shelf devices. We show analytically and experimentally that these solutions are highly vulnerable to impersonation attacks. We propose RF-Veil, a radiometric fingerprinting solution that not only is robust against impersonation attacks but also protects user privacy.
• Score: 8.89054576694426
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

Related papers

• Preventing Radio Fingerprinting through Friendly Jamming [5.074726108522963]
  Radio frequency fingerprinting enables a passive receiver to recognize and authenticate a transmitter without the need for cryptographic tools. We examine the hostile usage of radio frequency fingerprinting, which facilitates the unauthorized tracking of wireless devices in the field by malicious entities. We suggest a method to sanitize the transmitted signal of its fingerprint using a jammer, deployed on purpose to improve devices' anonymity on the channel.
  arXiv  Detail & Related papers  (2024-07-11T09:01:46Z)
• Erasing Radio Frequency Fingerprints via Active Adversarial Perturbation [19.88283575742985]
  We consider a common RF fingerprinting scenario, where machine learning models are trained from pilot signal data for identification. A novel adversarial attack solution is designed to generate proper perturbations, whereby the pilot signal can hide the hardware feature and misclassify the model. Extensive experiment results demonstrate that the RF fingerprints can be effectively erased to protect the user privacy.
  arXiv  Detail & Related papers  (2024-06-11T15:16:05Z)
• Sticky Fingers: Resilience of Satellite Fingerprinting against Jamming Attacks [13.857226688708353]
  We evaluate the effectiveness of radio fingerprinting techniques under interference and jamming attacks. We conclude that it takes a similar amount of jamming power in order to disrupt the fingerprint as it does to jam the message contents itself.
  arXiv  Detail & Related papers  (2024-02-07T17:28:09Z)
• Tamper-Evident Pairing [55.2480439325792]
  Tamper-Evident Pairing (TEP) is an improvement of the Push-Button configuration (PBC) standard. TEP relies on the Tamper-Evident Announcement (TEA), which guarantees that an adversary can neither tamper a transmitted message without being detected, nor hide the fact that the message has been sent. This paper provides a comprehensive overview of the TEP protocol, including all information needed to understand how it works.
  arXiv  Detail & Related papers  (2023-11-24T18:54:00Z)
• Secure and Privacy Preserving Proxy Biometrics Identities [25.272389610447856]
  This work proposes a novel approach for generating new artificial fingerprints also called proxy fingerprints. These proxy biometrics can be generated from original ones only with the help of a user-specific key. Using the proposed approach a proxy dataset is generated from samples belonging to Anguli fingerprint database. Matching experiments were performed on the new set which is 5 times larger than the original, and it was found that their performance is at par with 0 FAR and 0 FRR in the stolen key, safe key scenarios.
  arXiv  Detail & Related papers  (2022-12-21T07:02:11Z)
• Hierarchical Perceptual Noise Injection for Social Media Fingerprint Privacy Protection [106.5308793283895]
  fingerprint leakage from social media raises a strong desire for anonymizing shared images. To guard the fingerprint leakage, adversarial attack emerges as a solution by adding imperceptible perturbations on images. We propose FingerSafe, a hierarchical perceptual protective noise injection framework to address the mentioned problems.
  arXiv  Detail & Related papers  (2022-08-23T02:20:46Z)
• Locally Authenticated Privacy-preserving Voice Input [10.82818142802482]
  Service providers must authenticate their users, although individuals may wish to maintain privacy. Preserving privacy while performing authentication is challenging, particularly where adversaries can use biometric data to train transformation tools. We introduce a secure, flexible privacy-preserving system to capture and store an on-device fingerprint of the users' raw signals.
  arXiv  Detail & Related papers  (2022-05-27T14:56:01Z)
• Backdoor Attack against Speaker Verification [86.43395230456339]
  We show that it is possible to inject the hidden backdoor for infecting speaker verification models by poisoning the training data. We also demonstrate that existing backdoor attacks cannot be directly adopted in attacking speaker verification.
  arXiv  Detail & Related papers  (2020-10-22T11:10:08Z)
• Mind the GAP: Security & Privacy Risks of Contact Tracing Apps [75.7995398006171]
  Google and Apple have jointly provided an API for exposure notification in order to implement decentralized contract tracing apps using Bluetooth Low Energy. We demonstrate that in real-world scenarios the GAP design is vulnerable to (i) profiling and possibly de-anonymizing persons, and (ii) relay-based wormhole attacks that basically can generate fake contacts.
  arXiv  Detail & Related papers  (2020-06-10T16:05:05Z)
• Decentralized Privacy-Preserving Proximity Tracing [50.27258414960402]
  DP3T provides a technological foundation to help slow the spread of SARS-CoV-2. System aims to minimise privacy and security risks for individuals and communities.
  arXiv  Detail & Related papers  (2020-05-25T12:32:02Z)
• Towards Face Encryption by Generating Adversarial Identity Masks [53.82211571716117]
  We propose a targeted identity-protection iterative method (TIP-IM) to generate adversarial identity masks. TIP-IM provides 95%+ protection success rate against various state-of-the-art face recognition models.
  arXiv  Detail & Related papers  (2020-03-15T12:45:10Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.