WiFi-ID: Human Identification Using WiFi Signal

Jin Zhang, Bo Wei, Wen Hu, Salil S. Kanhere

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

99 Citations (Scopus)
12 Downloads (Pure)

Abstract

Prior research has shown the potential of device-free WiFi sensing for human activity recognition. In this paper, we show for the first time WiFi signals can also 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 channel state information 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. We conduct extensive experiments to demonstrate that our system 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.
Original languageEnglish
Title of host publication2016 International Conference on Distributed Computing in Sensor Systems (DCOSS)
PublisherIEEE
Pages75-82
Number of pages8
ISBN (Electronic)9781509014606
ISBN (Print)9781509014613
DOIs
Publication statusPublished - 26 May 2016

Fingerprint

Dive into the research topics of 'WiFi-ID: Human Identification Using WiFi Signal'. Together they form a unique fingerprint.

Cite this