Integrated Framework for Anonymous Biometric Key Based Identity Management System
P Suresh1, Radhika K R2

1P Suresh, Research Scholar, BMS College of Engineering, Bangalore, India.
2Radhika K R, Professor, Dept. of ISE, BMS College of Engineering, Bangalore, India.

Manuscript received on 01 August 2019. | Revised Manuscript received on 07 August 2019. | Manuscript published on 30 September 2019. | PP: 4594-4600-1 | Volume-8 Issue-3 September 2019 | Retrieval Number: C6831098319/2019©BEIESP | DOI: 10.35940/ijrte.C6831.098319
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: 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.
Keywords- Identity Management System, User Privacy, Consistent Keys, Clustering.

Scope of the Article:
Disaster Management