Continuous User Authentication Using IoT Wearable Sensors

• Published in: IEEE International Symposium on Circuits and Systems proceedings pp. 1 - 5
• Main Authors: Smyth, Conor, Wang, Guoxin, Panicker, Rajesh, Nag, Avishek, Cardiff, Barry, John, Deepu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.05.2021
• Subjects: Authentication; Continuous Authentication; Discrete cosine transforms; Dry Electrodes; ECG; Electrocardiography; Electrodes; Heart rate variability; IoT; Support vector machines; Wearable; Wearable computers
• ISBN: 9781728192017; 1728192013
• ISSN: 2158-1525
• DOI: 10.1109/ISCAS51556.2021.9401741

Over the past several years, the electrocardiogram (ECG) has been investigated for its uniqueness and potential to discriminate between individuals. This paper discusses how this discriminatory information can help in continuous user authentication by a wearable chest strap which uses dry electrodes to obtain a single lead ECG signal. To the best of the authors' knowledge, this is the first such work which deals with continuous authentication using a genuine wearable device as most prior works have either used medical equipment employing gel electrodes to obtain an ECG signal or have obtained an ECG signal through electrode positions that would not be feasible using a wearable device. Prior works have also mainly dealt with using the ECG signal for identification rather than verification, or dealt with using the ECG signal for discrete authentication. This paper presents a novel algorithm which uses QRS detection, weighted averaging, Discrete Cosine Transform (DCT), and a Support Vector Machine (SVM) classifier to determine whether the wearer of the device should be positively verified or not. Zero intrusion attempts were successful when tested on a database consisting of 33 subjects.