Salil Kanhere, University of New South Wales

Who Are You? New Approaches for Authentication in Smart Spaces

Abstract

Smart environments are increasingly offering a range of personalised services which require knowing the identity of the person currently using the space. Widely used authentication methods including fingerprint and face recognition have been shown to be vulnerable. In the first part of this talk, we present a human identification mechanism called Vein‐ID, that uses the vein pattern of an individual’s hand dorsum recorded using an off‐the‐shelf depth camera. Vein-ID extracts vein patterns using the depth information and infrared images. Two deep learning models are presented for precisely identifying a target individual from a set of enrolled users. We demonstrate using a comprehensive data set of approximately 17,500 images from 35 subjects that Vein-ID can identify an individual with an average accuracy of over 99%. In the second part of this talk, 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 Gate-ID that analyses the channel state information from ambient WiFi signals to extract unique features that are representative of that individual’s gait. Gate-ID uses a novel attention-based deep learning model that fuses various weighted features and ignores ineffective noise to uniquely identify individuals. We implement Gate-ID on commercial off-the-shelf devices and demonstrate that it can uniquely identify individuals with average accuracy of 90.7% to 75.7% from a group of 6 to 20 people, respectively. Both systems are resilient to attacks. Unlike other physical biometric identifiers, surreptitiously capturing an individuals’s vein pattern is difficult. Furthermore, mimicking an individual’s walking style is equally hard.

Bio

Salil Kanhere received the M.S. and Ph.D. degrees from Drexel University, Philadelphia, USA. He is a Professor of Computer Science and Engineering with UNSW Sydney, Australia. His research interests include the Internet of Things, cyber physical systems, blockchain, pervasive computing, cybersecurity, and applied machine learning. Salil is also affiliated with CISRO’s Data61 and the Cybersecurity Cooperative Research Centre. He is a Senior Member of the IEEE and ACM, an ACM Distinguished Speaker and an IEEE Computer Society Distinguished Visitor. He has received the Friedrich Wilhelm Bessel Research Award (2020) and the Humboldt Research Fellowship (2014), both from the Alexander von Humboldt Foundation in Germany. He has held visiting positions at I2R Singapore, Technical University Darmstadt, University of Zurich and Graz University of Technology. He serves as the Editor in Chief of the Ad Hoc Networks journal and as an Associate Editor of IEEE Transactions On Network and Service Management, Computer Communications, and Pervasive and Mobile Computing. He regularly serves on the organising committee of IEEE/ACM international conferences in the domain. He co-authored a book titled Blockchain for Cyberphysical Systems which was published by Artech House in 2020. Further details are at: https://salilkanhere.net.