Privacy Preserving Fingerprint Matching

Julia Mader

Privacy Preserving Fingerprint Matching

Julia Mader

Publikation: Abschlussarbeit › Masterarbeit

Abstract

This thesis focuses on implementing and optimizing a minutiae-based fingerprint matching algorithm with Multiparty Computation (MPC), addressing the challenge of maintaining privacy while ensuring reasonable computation times. The author presents an implementation using the minutiae-based matcher SourceAFIS, optimized for MPC, and evaluates its performance to assess if current protocols are ready for deployment in time critical scenarios. Results show promise, emphasizing our ongoing research to achieve a fully-fledged MPC implementation with high accuracy.

Originalsprache	Englisch
Qualifikation	Master of Science
Gradverleihende Hochschule	Technische Universität München
Betreuer/-in / Berater/-in	Lorünser, Thomas, Betreuer:in
Datum der Bewilligung	12 Sept. 2023
Publikationsstatus	Veröffentlicht - 12 Sept. 2023

Research Field

Cyber Security

Schlagwörter

Multiparty Computation
Fingerprint Matching
Verschlüsselung
Kryptographie

Diese Publikation zitieren

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AB - This thesis focuses on implementing and optimizing a minutiae-based fingerprint matching algorithm with Multiparty Computation (MPC), addressing the challenge of maintaining privacy while ensuring reasonable computation times. The author presents an implementation using the minutiae-based matcher SourceAFIS, optimized for MPC, and evaluates its performance to assess if current protocols are ready for deployment in time critical scenarios. Results show promise, emphasizing our ongoing research to achieve a fully-fledged MPC implementation with high accuracy.

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