Biometric based Consistent Key Generation for IMS

Security and user privacy are areas of concern in digital transactions over a network. Integration of biometric pattern matching into an identity management system (IMS) enhances security of transactions and improves ease of use. Privacy of users in a biometric based system is improved by using keys generated directly from feature sets instead of conventional stored templates. This paper proposes a framework for integrating biometric key based authentication into an IMS. The generated keys need to be consistent. Consistency of keys is attained if the same key is generated for every instance of biometric input. Generation of long and consistent keys directly from feature sets poses a challenge due to intra and inter user variations inherent to biometric data. A novel methodology for generating consistent keys using principles of vector quantization and cluster based learning is introduced. 15-bit keys have been extracted from handwritten signature datasets. The results are promising and can be extended to multi-modal biometric feature sets.