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Probe Request Based Device Identification Attack and Defense

机译:基于探测要求的设备识别攻击和防御

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摘要

Wi-Fi network has an open nature so that it needs to face greater security risks compared to wired network. The MAC address represents the unique identifier of the device, and is easily obtained by an attacker. Therefore MAC address randomization is proposed to protect the privacy of devices in a Wi-Fi network. However, implicit identifiers are used by attackers to identify user’s device, which can cause the leakage of user’s privacy. We propose device identification based on 802.11ac probe request frames. Here, a detailed analysis on the effectiveness of 802.11ac fields is given and a novel device identification method based on deep learning whose average f1-score exceeds 99% is presented. With a purpose of preventing attackers from obtaining relevant information by the device identification method above, we design a novel defense mechanism based on stream cipher. In that case, the original content of probe request frame is hidden by encrypting probe request frames and construction of probe request is reserved to avoid the finding of attackers. This defense mechanism can effectively reduce the performance of the proposed device identification method whose average f1-score is below 30%. In general, our research on attack and defense mechanism can preserve device privacy better.
机译:与有线网络相比,Wi-Fi网络具有开放性,使其需要面对更大的安全风险。 MAC地址表示设备的唯一标识符,并且由攻击者轻松获得。因此,提出了MAC地址随机化以保护Wi-Fi网络中设备的隐私。但是,攻击者使用隐式标识符来识别用户的设备,这可能导致用户的隐私泄漏。我们提出基于802.11ac探针请求帧的设备识别。这里,给出了对802.11ac字段的有效性的详细分析,并提出了基于深度学习的新型设备识别方法,其平均F1分数超过99%。目的是防止攻击者通过上面的设备识别方法获得相关信息,我们设计了一种基于流密码的新型防御机制。在这种情况下,通过加密探测请求帧隐藏探测请求帧的原始内容,并保留探测请求的构造,以避免发现攻击者。这种防御机制可以有效地降低所提出的设备识别方法的性能,其平均F1分数低于30%。一般来说,我们对攻击和防御机制的研究可以更好地保护设备隐私。

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