Implementation of measures to ensure security of transactions while ensuring privacy of user credentials is an area of challenge 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 long, reproducible with high integrity and need to possess sufficient entropy. Generation of keys directly from feature traits poses a challenge due to intra and inter user variations inherent to biometric data. A novel methodology for generating and integrating crytpo keys into an identity management system is proposed. The keys have been extracted from iris trait. 300 bits keys have been extracted from iris datasets. The results are promising and can be extended to multi-modal biometric feature sets.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.