Genetic & Evolutionary Biometric Security: Disposable Feature Extractors for Mitigating Biometric Replay Attacks

Abstract

Biometric-based access control systems (BACSs) are vulnerable to replay attacks. Replay attacks occur when a biometric template is intercepted and maliciously used to gain unauthorized access to a system. In this paper, we introduce a Genetic and Evolutionary Biometric Security (GEBS) application which uses a Genetic and Evolutionary Computation to develop disposable Feature Extractors (FEs) in an effort to mitigate replay attacks. We describe how a previously developed system known as GEFE (Genetic and Evolutionary Feature Extraction) can be used to evolve unique and disposable FEs for users of BACS. Furthermore, we propose two access control protocols based on the use of disposable FEs and/or their resulting templates (also referred to as feature vectors (FVs)). In our proposed protocols, FEs/FVs are used to authenticate the identity of individuals and are then discarded. Our results show that this GEBS application can be successfully used to mitigate biometric replay attacks.