WiSafe:A Real-Time System for Intrusion Detection Based on WiFi Signals
Pioneer research works for WiFi-based sensing usually depend on an extremely high sampling rate of over 1000 Hz to collect an abundant number of Channel State Information(CSI)measure-ments,which depict the environmental changes and human mo-tions.However,these methodologies can be hardly deployed on embedded platforms and cannot be directly commercialized.In this paper,we propose WiSafe,a real-time intrusion detection sys-tem that works with a relatively low sampling rate of 15-20 Hz on commercial embedded devices.Both primitive physical features and high-level CSI-based features are adopted as the input of the classification methods.We exploit MLP,TextCNN and Bi-LSTM together for majority voting to improve the detection accuracy and robustness.Experiment results demonstrate that WiSafe achieves an accuracy of 97.8%(AUC=0.9931)that is comparable to those of previous works even with a low sampling rate,and can run in real time,which make it permissible for practical use.
WiFi Channel State Information Low Sampling Embedded De-vice Real-time Detection
Yu Bao Liang Dong Yue Zheng Ying Liu
Tsinghua University LiaoNing Technical University
国际会议
2019国图灵大会(ACM Turing Celebration conference-China 2019 )
成都
英文
475-479
2019-05-17（万方平台首次上网日期，不代表论文的发表时间）