Passive WiFi Sensing for Identification and Authentication

Speaker:  Salil Kanhere – Sydney, NSW, Australia
Topic(s):  Networks and Communications


Wireless devices are everywhere - our homes, offices, shops, restaurants and virtually all of our urban spaces. They invisibly fill the air with a spectrum of Radio Frequency (RF) signals. Any actions (e.g., gestures) undertaken by a human being creates perturbations in this ambient RF field. Analysis of the Channel State Information (CSI), which captures fine-grained details of the RF channel properties reveals a strong potential for recognizing these actions. In this talk, we will highlight two applications of passive WiFi sensing. In the first instance, we show that WiFi signals can be used to uniquely identify people. There is strong evidence that suggests that all humans have a unique gait. An individual's gait will thus create unique perturbations in the WiFi spectrum. We propose a system called WiFi-ID that analyses the CSI to extract unique features that are representative of the walking style of that individual and thus allow us to uniquely identify that person. We implement WiFi-ID on commercial off-the-shelf devices and show that it can uniquely identify people with average accuracy of 93% to 77% from a group of 2 to 6 people, respectively. We envisage that this technology can find many applications in small office or smart home settings. In the second part of the talk we present a two-factor authentication system called Wi-Auth, which utilizes WiFi signals for establishing the close proximity between a pre-registered secondary device and the primary device from which the login attempt is being made. We use this proximity as a second factor of authentication while requiring very limited interaction from the user. We implement Wi-Auth on commodity devices and demonstrate that it can achieve 94% authentication accuracy with 5% false positives and 6% false negatives. Moreover, Wi-Auth is robust in preventing co-located attacks with a 95% detection accuracy. 

About this Lecture

Number of Slides:  45
Duration:  60 minutes
Languages Available:  English
Last Updated: 

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