An Integrated Soft Computing Approach to a Multi-biometric Security Model

TL;DR

This paper introduces a soft computing framework for multi-biometric security that adaptively fuses biometric and biographical data, improving accuracy and efficiency through novel comparison techniques and real-time decision-making.

Contribution

It presents a new adaptive fusion framework, a novel string comparison method, and a scientific approach for evaluating fusion efficiency in biometric security.

Findings

Enhanced accuracy by selective data fusion

Reduced computational effort through adaptive decision-making

Effective comparison of fusion strategies using effort to error analysis

Abstract

The abstract of the thesis consists of three sections, videlicet, Motivation Chapter Organization Salient Contributions. The complete abstract is included with the thesis. The final section on Salient Contributions is reproduced below. Salient Contributions The research presents the following salient contributions: i. A novel technique has been developed for comparing biographical information, by combining the average impact of Levenshtein, Damerau-Levenshtein, and editor distances. The impact is calculated as the ratio of the edit distance to the maximum possible edit distance between two strings of the same lengths as the given pair of strings. This impact lies in the range [0, 1] and can easily be converted to a similarity (matching) score by subtracting the impact from unity. ii. A universal soft computing framework is proposed for adaptively fusing biometric and biographical information by making real-time decisions to determine after consideration of each individual identifier whether computation of matching scores and subsequent fusion of additional identifiers, including biographical information is required. This proposed framework not only improves the accuracy of the system by fusing less reliable information (e.g. biographical information) only for instances where such a fusion is required, but also improves the efficiency of the system by computing matching scores for various available identifiers only when this computation is considered necessary. iii. A scientific method for comparing efficiency of fusion strategies through a predicted effort to error trade-off curve.