A Smart Hardware Security Engine Combining Entropy Sources of ECG, HRV, and SRAM PUF for Authentication and Secret Key Generation

Sai Kiran Cherupally, Shihui Yin, Deepak Kadetotad, Chisung Bae, Sang Joon Kim, Jae Sun Seo

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Securing personal data in wearable devices is becoming a crucial necessity as wearable devices are being deployed ubiquitously, which inadvertently exposes them to more sophisticated adversarial attacks. Although authentication systems using a single-entropy source, such as fingerprint or iris, are being used widely, successful spoofing attacks have been made, which show such systems' vulnerability. To mitigate these issues, new biometric modalities [e.g., electrocardiogram (ECG) and photoplethysmogram (PPG)], as well as multifactor authentication/security engine designs, are being investigated. In this work, we present a new smart hardware security engine that combines three different sources of entropy, ECG, heart rate variability (HRV), and SRAM-based physical unclonable function (PUF) to perform real-Time authentication and generate unique/random signatures. Such hybrid signatures vary person-To-person, device-To-device, and over time, which significantly reduces the scope of an attack and enables secure personal device authentication as well as secret random key generation. The prototype chip fabricated in 65-nm LP CMOS consumes 4.04\mu \text{W} at 0.6 V for real-Time authentication. Compared with ECG-only authentication, the average equal error rate of multi-source authentication is reduced by 7\times down to 0.2375% for a 741-subject in-house ECG database. The generalization capability of the hardware was also tested by evaluating equal error rate (EER) values using other ECG databases available online. Also, 256-bit keys generated by optimally combining ECG, HRV, and PUF values fully pass nine NIST randomness tests.

Original languageEnglish (US)
Article number9152094
Pages (from-to)2680-2690
Number of pages11
JournalIEEE Journal of Solid-State Circuits
Volume55
Issue number10
DOIs
StatePublished - Oct 2020
Externally publishedYes

Keywords

  • Biometric authentication
  • SRAM
  • electrocardiogram (ECG)
  • feature extraction
  • multi-factor authentication
  • physical unclonable function (PUF)
  • secret key generation

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'A Smart Hardware Security Engine Combining Entropy Sources of ECG, HRV, and SRAM PUF for Authentication and Secret Key Generation'. Together they form a unique fingerprint.

Cite this