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

Sheng, Weiguo and Howells, Gareth and Fairhurst, Michael and 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 . (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)

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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
Uncontrolled keywords: biometric authentication; clustering; feature evaluation; handwritten signatures; security
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics (see also: telecommunications) > TK7880 Applications of electronics (inc industrial & domestic) > TK7882.B56 Biometrics
Divisions: Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: J. Harries
Date Deposited: 20 Apr 2009 14:32
Last Modified: 23 May 2014 09:22
Resource URI: https://kar.kent.ac.uk/id/eprint/15843 (The current URI for this page, for reference purposes)
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