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

Renato Cordeiro, Dhruv Gajaria, Ankur Limaye, Tosiron Adegbija, Nima Karimian, Fatemeh Tehranipoor

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

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.

Original languageEnglish (US)
Article number9229109
Pages (from-to)3373-3384
Number of pages12
JournalIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Volume39
Issue number11
DOIs
StatePublished - Nov 2020

Keywords

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

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering

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