Wi-Alarm: Low-Cost Passive Intrusion Detection Using WiFi

作者：Tao Wang, Dandan Yang, Shunqing Zhang, Yating Wu, Shugong Xu · 发表于：Sensors · 年份：2019 · DOI：10.3390/s19102335 · 被引用次数：51 · 研究领域：Indoor and Outdoor Localization Technologies、Wireless Networks and Protocols、Millimeter-Wave Propagation and Modeling

In this paper, we present a WiFi-based intrusion detection system called Wi-Alarm. Motivated by our observations and analysis that raw channel state information (CSI) of WiFi is sensitive enough to monitor human motion, Wi-Alarm omits data preprocessing. The mean and variance of the amplitudes of raw CSI data are used for feature extraction. Then, a support vector machine (SVM) algorithm is applied to determine detection results. We prototype Wi-Alarm on commercial WiFi devices and evaluate it in a typical indoor scenario. Results show that Wi-Alarm reduces much computational expense without losing accuracy and robustness. Moreover, different influence factors are also discussed in this paper.