ECG-Based Authentication Using Timing-Aware Domain-Specific Architecture

Publication Date

11-1-2020

Document Type

Article

Publication Title

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems

Volume

39

Issue

11

DOI

10.1109/TCAD.2020.3012169

First Page

3373

Last Page

3384

Abstract

Electrocardiogram (ECG) biometric authentication (EBA) is a promising approach for human identification, particularly in consumer devices, due to the individualized, ubiquitous, and easily identifiable nature of ECG signals. Thus, computing architectures for EBA must be accurate, fast, energy efficient, and secure. In this article, first, we implement an EBA algorithm to achieve 100% accuracy in user authentication. Thereafter, we extensively analyze the algorithm to show the distinct variance in execution requirements and reveal the latency bottleneck across the algorithm's different steps. Based on our analysis, we propose a domain-specific architecture (DSA) to satisfy the execution requirements of the algorithm's different steps and minimize the latency bottleneck. We explore different variations of the DSA, including one that features the added benefit of ensuring constant timing across the different EBA steps, in order to mitigate the vulnerability to timing-based side-channel attacks. Our DSA improves the latency compared to a base ARM-based processor by up to $4.24\times $ , while the constant timing DSA improves the latency by up to 19%. Also, our DSA improves the energy by up to $5.59\times $ , as compared to the base processor.

Funding Number

1844952

Funding Sponsor

National Science Foundation

Keywords

Biometric authentication, domain-specific architectures (DSAs), electrocardiogram (ECG), energy efficient, Internet of Biometric Things (IoBT), Internet of Things (IoT), secure architectures, side-channel attacks

Department

Computer Engineering

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