Device-Free Passive Identity Identification via WiFi Signals

Sensors
Jiguang LvDapeng Man

Abstract

Device-free passive identity identification attracts much attention in recent years, and it is a representative application in sensorless sensing. It can be used in many applications such as intrusion detection and smart building. Previous studies show the sensing potential of WiFi signals in a device-free passive manner. It is confirmed that human's gait is unique from each other similar to fingerprint and iris. However, the identification accuracy of existing approaches is not satisfactory in practice. In this paper, we present Wii, a device-free WiFi-based Identity Identification approach utilizing human's gait based on Channel State Information (CSI) of WiFi signals. Principle Component Analysis (PCA) and low pass filter are applied to remove the noises in the signals. We then extract several entities' gait features from both time and frequency domain, and select the most effective features according to information gain. Based on these features, Wii realizes stranger recognition through Gaussian Mixture Model (GMM) and identity identification through a Support Vector Machine (SVM) with Radial Basis Function (RBF) kernel. It is implemented using commercial WiFi devices and evaluated on a dataset with more than 1500 gait inst...Continue Reading

Citations

Aug 23, 2020·Sensors·Xiaochao DangYang Liu
Apr 16, 2020·Sensors·Masakatsu Ogawa, Hirofumi Munetomo
Oct 23, 2019··Liviu-Mihai CalinKean Walmsley

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Methods Mentioned

BETA
feature extraction
PCA

Software Mentioned

ID
WiWho
WiDraw
WifiU
Wii
WiFi
Linux
Ubuntu
eyes
WiFinger

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