JOURNAL ARTICLE

Privacy-preserving continuous authentication using behavioral biometrics

Ahmed Fraz BaigSigurd EskelandBian Yang

Year: 2023 Journal:   International Journal of Information Security Vol: 22 (6)Pages: 1833-1847   Publisher: Springer Science+Business Media

Abstract

Abstract Continuous authentication modalities collect and utilize users’ sensitive data to authenticate them continuously. Such data contain information about user activities, behaviors, and other demographic information, which causes privacy concerns. In this paper, we propose two privacy-preserving protocols that enable continuous authentication while preventing the disclosure of user-sensitive information to an authentication server. We utilize homomorphic cryptographic primitives that protect the privacy of biometric features with an oblivious transfer protocol that enables privacy-preserving information retrieval. We performed the biometric evaluation of the proposed protocols on two datasets, a swipe gesture dataset and a keystroke dynamics dataset. The biometric evaluation shows that the protocols have very good performance. The execution time of the protocols is measured by considering continuous authentication using: only swipe gestures, keystroke dynamics, and hybrid modalities. The execution time proves the protocols are very efficient, even on high-security levels.

Keywords:
SwIPe Computer science Biometrics Keystroke dynamics Homomorphic encryption Authentication (law) Computer security Protocol (science) Cryptography Spoofing attack Keystroke logging Information sensitivity Cryptographic protocol Encryption Password S/KEY

Metrics

18
Cited By
11.13
FWCI (Field Weighted Citation Impact)
25
Refs
0.98
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

User Authentication and Security Systems
Physical Sciences →  Computer Science →  Information Systems
Biometric Identification and Security
Physical Sciences →  Computer Science →  Signal Processing
Advanced Steganography and Watermarking Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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