TY - JOUR
T1 - ECG-Based Authentication Using Timing-Aware Domain-Specific Architecture
AU - Cordeiro, Renato
AU - Gajaria, Dhruv
AU - Limaye, Ankur
AU - Adegbija, Tosiron
AU - Karimian, Nima
AU - Tehranipoor, Fatemeh
N1 - Funding Information:
Manuscript received April 17, 2020; revised June 9, 2020; accepted July 6, 2020. Date of publication October 19, 2020; date of current version October 27, 2020. This work was supported in part by the National Science Foundation under Grant CNS-1844952. This article was presented in the International Conference on Hardware/Software Codesign and System Synthesis 2020 and appears as part of the ESWEEK-TCAD special issue. (Corresponding author: Tosiron Adegbija.) Renato Cordeiro and Nima Karimian are with the Department of Computer Engineering, San José State University, San Jose, CA 95192 USA (e-mail: renato.silveiracordeiro@sjsu.edu; nima.karimian@sjsu.edu).
Publisher Copyright:
© 1982-2012 IEEE.
PY - 2020/11
Y1 - 2020/11
N2 - 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.
AB - 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.
KW - Biometric authentication
KW - Internet of Biometric Things (IoBT)
KW - Internet of Things (IoT)
KW - domain-specific architectures (DSAs)
KW - electrocardiogram (ECG)
KW - energy efficient
KW - secure architectures
KW - side-channel attacks
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U2 - 10.1109/TCAD.2020.3012169
DO - 10.1109/TCAD.2020.3012169
M3 - Article
AN - SCOPUS:85096031339
VL - 39
SP - 3373
EP - 3384
JO - IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
JF - IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
SN - 0278-0070
IS - 11
M1 - 9229109
ER -