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

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ID: 88129
2019
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Abstract
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.
Reference Key
wang2019wialarmsensors Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Wang, Tao;Yang, Dandan;Zhang, Shunqing;Wu, Yating;Xu, Shugong;
Journal sensors
Year 2019
DOI
E2335
URL
Keywords
wifi low cost csi device-free passive detection

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