Multi-biometric template protection — A security analysis of binarized statistical features for bloom filters on smartphones
Martin Stokkenes, Raghavendra Ramachandra, Morten K. Sigaard, Kiran Bylappa Raja, Marta Gomez‐Barrero, Christoph Busch · 2016
In recent years, we have seen huge growth of biometric systems incorporated in devices such as smartphones and security is one of the major concerns. In this work a multi-biometric template protected system is proposed, based on Bloom filers and binarized statistical image features (BSIF). Features are extracted from face and both periocular regions and templates protected using Bloom filters. Score level fusion is applied to increase recognition accuracy. The system is tested on a database, consisting of 94 subjects, of images collected with smart phones. A comparison between unprotected and protected templates in the system shows the feasibility of the template protection method with observed Genuine-Match-Rate (GMR) of 95.95% for unprotected templates and 91.61% at a False-Match-Rate (FMR) of 0.01%. Irreversibility and unlinkability of the system is analysed based on a recently published security evaluation framework.