ZK-SERIES: Privacy-Preserving Authentication using Temporal Biometric Data
Daniel Reijsbergen, Eyasu Getahun Chekole, Howard Halim, Jianying Zhou

TL;DR
ZK-SERIES introduces a privacy-preserving biometric authentication protocol using zero-knowledge proofs for time series data, optimized for low-capacity devices, achieving practical performance on older smartphones.
Contribution
It presents ZK-SERIES, a novel zero-knowledge proof-based framework for secure, efficient biometric authentication with temporal data, suitable for resource-constrained devices.
Findings
Authentication completed within 1.3 seconds on old smartphones
Effective privacy preservation for biometric time series data
Scalability demonstrated with artificial data
Abstract
Biometric authentication relies on physiological or behavioral traits that are inherent to a user, making them difficult to lose, forge or forget. Biometric data with a temporal component enable the following authentication protocol: recent readings of the underlying biometrics are encoded as time series and compared to a set of base readings. If the distance between the new readings and the base readings falls within an acceptable threshold, then the user is successfully authenticated. Various methods exist for comparing time series data, such as Dynamic Time Warping (DTW) and the Time Warp Edit Distance (TWED), each offering advantages and drawbacks depending on the context. Moreover, many of these techniques do not inherently preserve privacy, which is a critical consideration in biometric authentication due to the complexity of resetting biometric credentials. In this work, we…
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Taxonomy
TopicsBiometric Identification and Security · User Authentication and Security Systems
