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Template-Free Biometric-Key Generation by Means of Fuzzy Genetic Clustering

Sheng, Weiguo, Howells, Gareth, Fairhurst, Michael, Deravi, Farzin (2008) Template-Free Biometric-Key Generation by Means of Fuzzy Genetic Clustering. IEEE Transactions on Information Forensics and Security, 3 (2). pp. 183-191. ISSN 1556-6013. (doi:10.1109/TIFS.2008.922056) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:15843)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1109/TIFS.2008.922056

Abstract

Biometric authentication is increasingly gaining popularity in a wide range of applications. However, the storage of the biometric templates and/or encryption keys that are necessary for such applications is a matter of serious concern, as the compromise of templates or keys necessarily compromises the information secured by those keys. In this paper, we propose a novel method, which requires storage of neither biometric templates nor encryption keys, by directly generating the keys from statistical features of biometric data. An outline of the process is as follows: given biometric samples, a set of statistical features is first extracted from each sample. On each feature subset or single feature, we model the intra and interuser variation by clustering the data into natural clusters using a fuzzy genetic clustering algorithm. Based on the modelling results, we subsequently quantify the consistency of each feature subset or single feature for each user. By selecting the most consistent feature subsets and/or single features for each user individually, we generate the key reliably without compromising its relative security. The proposed method is evaluated on handwritten signature data and compared with related methods, and the results are very promising.

Item Type: Article
DOI/Identification number: 10.1109/TIFS.2008.922056
Uncontrolled keywords: biometric authentication; clustering; feature evaluation; handwritten signatures; security
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics > TK7880 Applications of electronics > TK7882.B56 Biometric identification
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: J. Harries
Date Deposited: 20 Apr 2009 14:32 UTC
Last Modified: 16 Nov 2021 09:53 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/15843 (The current URI for this page, for reference purposes)

University of Kent Author Information

Sheng, Weiguo.

Creator's ORCID:
CReDIT Contributor Roles:

Howells, Gareth.

Creator's ORCID: https://orcid.org/0000-0001-5590-0880
CReDIT Contributor Roles:

Fairhurst, Michael.

Creator's ORCID:
CReDIT Contributor Roles:

Deravi, Farzin.

Creator's ORCID: https://orcid.org/0000-0003-0885-437X
CReDIT Contributor Roles:
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