Adaptive and Distributed Cryptography for Signature Biometrics Protection

摘要

The most emerging technology for people identification and authentication is biometrics. In contrast with traditional recognition approaches, biometric authentication relies on who a person is or what a person does, being based on strictly personal traits, much more difficult to be forgotten, lost, stolen, copied or forged than traditional data. In this paper, we focus on two vulnerable points of biometric systems: the database where the templates are stored and the communication channel between the stored templates and the matcher. Specifically, we propose a method, based on user adaptive error correction codes, to achieve securitization and cancelability of the stored templates applied to dynamic signature features. More in detail, the employed error correction code is tailored to the intra-class variability of each user's signature features. This leads to an enhancement of the system performance expressed in terms of false acceptance rate. Moreover, in order to avoid corruption or interception of the stored templates in the transmission channels, we propose a scheme based on threshold cryptography: the distribution of the certificate authority functionality among a number of nodes provides distributed, fault-tolerant, and hierarchical key management services. Experimental results show the effectiveness of our approach, when compared to traditional non-secure correlation-based classifiers.