  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.
