A real-time and robust intrusion detection system with commodity wi-fi

Shengjie Li (1) , Zhaopeng Liu (1) , Yue Zhang (1) , Xiaopeng Niu (1) , Leye Wang (1) , Daqing Zhang (1, 2, 3, 4, 5)

1 Peking University [Beijing]
2 ACMES-SAMOVAR - Architecture, Cloud continuum, formal Models, artificial intElligence and Services in distributed computing
3 TSP - RS2M - Département Réseaux et Services Multimédia Mobiles
4 IP Paris - Institut Polytechnique de Paris
5 CNRS - Centre National de la Recherche Scientifique

Intrusion detection plays a rather important role in many applications, like asset protection and elder caring. Since we cannot make any requirements on the intruder, a device-free passive way of intrusion detection is much more promising and practical. In order to achieve robust passive intrusion detection, various techniques have been proposed, including video-based, infra-based and sensor-based approaches, among which dedicated device installation is often required. In this work, we present a real-time and robust device-free intrusion detection system, named RR-Alarm. By reusing the existing Wi-Fi signals, RR-Alarm is able to detect human intrusion in real time, at the same time, requiring no additional facilities installation. By utilizing the Doppler effects incurred by human motion on multiple Wi-Fi devices, RR-Alarm is not only able to accurately detect the intrusion without any extra human efforts but also avoids a large number of false alarms caused by the human motion from outside the house. A long-term trial in a nursing home verifies the effectiveness of our Wi-Fi based RR-Alarm system.

Mots clés: Wi-Fi; Channel State Information (CSI); Intrusion detection; Device-free sensing

Domaines: Informatique ubiquitaire

Shengjie Li, Zhaopeng Liu, Yue Zhang, Xiaopeng Niu, Leye Wang, et al.. A real-time and robust intrusion detection system with commodity wi-fi. UbiComp/ISWC 2019 Adjunct: 2019 ACM international joint conference on Pervasive and Ubiquitous Computing and International Symposium on Wearable Computers, Sep 2019, London, United Kingdom. pp.316-319, ⟨10.1145/3341162.3343789⟩. ⟨hal-03002793⟩