Secur-Fi: A Secure Wireless Sensing System Based on Commercial Wi-Fi Devices
Xuanqi Meng, Jiarun Zhou, Xiulong Liu, Xinyu Tong, Wenyu Qu, Jianrong Wang
摘要
Wi-Fi sensing technology plays an important role in numerous IoT applications such as virtual reality, smart homes and elder healthcare. The basic principle is to extract physical features from the Wi-Fi signals to depict the user’s locations or behaviors. However, current research focuses more on improving the sensing accuracy but neglects the security concerns. Specifically, current Wi-Fi router usually transmits a strong signal, so that we can access the Internet even through the wall. Accordingly, the outdoor adversaries are able to eavesdrop on this strong Wi-Fi signal, and infer the behavior of indoor users in a non-intrusive way, while the indoor users are unaware of this eavesdropping. To prevent outside eavesdropping, we propose Secur-Fi, a secure Wi-Fi sensing system. Our system meets the following two requirements: (1) we can generate fraud signals to block outside unauthorized Wi-Fi sensing; (2) we can recover the signal, and enable authorized Wi-Fi sensing. We implement the proposed system on commercial Wi-Fi devices and conduct experiments in three applications including passive tracking, behavior recognition, and breath detection. The experiment results show that our proposed approaches can reduce the accuracy of unauthorized sensing by 130% (passive tracking), 72% (behavior recognition), 86% (breath detection).
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