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.

中文翻译：

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保持连接状态，畅通无阻：通过模糊辐射指纹来增强WiFi的安全性和隐私性

WiFi芯片组固有的硬件缺陷会在传输的信号中体现出来，从而导致独特的辐射指纹。此指纹可以用作增强安全性的其他身份验证手段。事实上，最近的工作提出了实用的指纹识别解决方案，可以在现成的商用设备中轻松实现。在本文中，我们通过分析和实验证明了这些解决方案非常容易受到模拟攻击。我们还证明，可以通过跟踪用户设备来滥用这种基于设备的唯一签名来侵犯隐私，并且直到今天，用户除了关闭设备之外，没有任何防止此类隐私攻击的手段。我们提出RF-Veil，一种辐射指纹识别解决方案，该解决方案不仅针对假冒攻击具有鲁棒性，而且还通过混淆非合法接收者的发射器的辐射指纹来保护用户隐私。具体来说，我们向传输的信号引入随机的相位误差模式，这样只有目标接收器才能提取发射器的原始指纹。在一系列实验和分析中，我们揭露了将天真的随机化方法用于统计攻击的脆弱性，并介绍了对策。最后，我们通过实验展示了RF-Veil在保护用户隐私和增强安全性方面的功效。更重要的是，我们提出的解决方案允许与不使用RF-Veil的其他设备进行通信。