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Open AccessArticle

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

Shanghai Institute for Advanced Communication and Data Science, Key laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai University, Shanghai 200444, China
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Sensors 2019, 19(10), 2335; https://doi.org/10.3390/s19102335
Received: 25 March 2019 / Revised: 18 April 2019 / Accepted: 22 April 2019 / Published: 21 May 2019
(This article belongs to the Special Issue Sensors In Target Detection)
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. View Full-Text
Keywords: WiFi; device-free passive detection; CSI; low cost WiFi; device-free passive detection; CSI; low cost
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MDPI and ACS Style

Wang, T.; Yang, D.; Zhang, S.; Wu, Y.; Xu, S. Wi-Alarm: Low-Cost Passive Intrusion Detection Using WiFi. Sensors 2019, 19, 2335.

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