Fuzzy evaluation of biometric authentication systems (original) (raw)
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The Concept of Application of Fuzzy Logic in Biometric Authentication Systems
Advances in Soft Computing
In the paper the key topics concerning architecture and rules of working of biometric authentication systems were described. Significant role is played by threshold which constitutes acceptance or rejection given authentication attempt. Application of elements of fuzzy logic was proposed in order to define threshold value of authentication system. The concept was illustrated by an example.
Decision Making in Multi-Biometric Systems Based on Fuzzy Integrals
Annotation. Use of fuzzy integrals is proposed for aggregation of classifiers results in multi-biometric systems. It is significantly better than application of a single classifier. Also, advantages and disadvantages of application of fuzzy integral method are reviewed.
Integrated Biometric Verification System Using Soft Computing Approach
Neural Processing Letters, 2007
Among various biometric verification systems, fingerprint verification is one of the most reliable and widely accepted. One essential part of fingerprint verification is the minutiae extraction system. Most existing minutiae extraction methods require image preprocessing or post processing resulting in additional complex computation and time. Hence, direct gray-scale minutiae extraction approach on the image is preferred. One of these approaches is the use of Fuzzy Neural Network (FNN) as a recognition system to detect the presence of minutiae pattern. Currently, the development of FNN as a tool of recognition has shown a promising prospect. Some researchers have proposed several types of FNN. In particular, a Generic Self Organizing Fuzzy Neural Network (GENSOFNN) has been shown to excel in comparison with other FNN. Therefore, a new approach to perform direct grayscale minutiae extraction based on GENSOFNN is proposed in this paper. Experimental results show the potential of using GENSOFNN for real-time point of sale (POS) terminal for verification.
Role of Fuzzy in Multimodal Biometrics System
Person identification is possible through the biometrics using their physiological and behavioral characteristics such as face, ear, thumb print, voice, signature and key stock. Unimodal biometric systems face a range of problems, including noisy data, intra-class versions, small liberty, non-university, spoof assaults, and unsustainable error rates. Some of these drawbacks can be overcome by multimodal biometric technologies, which incorporate data from various information sources. In this paper we work on multimodal biometric using three modalities face, ear and foot to find the optimal results using fuzzy fusion mechanism and produces final identification decision via a fuzzy rules that enhance the quality of multimodalities biometric system.
Classification and Performance of Biometric Authentication
International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2021
Out of the many authentication schemes in this paper we are trying to focus on the performance and classification of one of the techniques of authentication that is the biometric authentication. Although efforts of the entire international biometric community, the measurement of accuracy of a biometric system is far to be completely investigated and, eventually, standardized. The paper presents a critical analysis of the measurement of an accuracy and performance of a biometric system.
An Investigation towards Effectiveness of Present State of Biometric-Based Authentication System
The adoption of biometric-based authentication mechanism has been already initiated a decade back but still in real-life we get to see usage of only unimodal biometrics. Out of all the different forms of biometrics, we see usage of fingerprint as the dominant attribute in contrast to different other attributes e.g. teeth image, palm, facial geometry, retina network, iris, etc. Multimodal biometrics is believed to offered better security compared to unimodal. Although, there are some of the technical advancement in evolving up with new multimodal methodologies, but still commercial usage of such is yet to be seen. Therefore, this manuscripts aims to explore the level of effectiveness in existing approaches of biometric-based authentication system in order to further investigate the unaddressed solution towards this problem. This paper reviews the approaches used for addressing different problems associated with biometrics and discusses about their technical methodologies as well as their limitations.
Comparative and Analysis Study of Biometric Systems
2019
In recent years, there has been a growing interest in the field of biometrics as a powerful identification technology. Various biometric technologies are based on behavioral and physiological analysis; therefore they must be reliable, robust, simple and cheap. In this paper, we have investigated an analytical comparison of different biometric systems namely: fingerprint, iris, face, voice, keystroke dynamics, signature, retina, etc. and we have classified these methods based on several criteria such as: universality, uniqueness, permanency, intrusiveness, effort, cost, and reliability, as well as the most used biometric systems requested in the market and those that are of greater interest in the current research work, and for each criteria we gave synthetic discussions. Furthermore, we provided a brief overview of biometric methods, then we have described the modes used in a biometric system such as enrollment, verification and identification and we have presented the possible appl...
Fuzzy aproach in biometric authentication by keystroke dynamics
2005
A person's identity verification became very important in information society. This article presents some results of our research of biometric authentication by keystroke dynamics. The comparison of the stochastic approach and using fuzzy numbers is presented as well.
Advances in Intelligent Systems and Computing, 2018
Feature extraction for an optimal data representation is crucial for any biometric identification system. In this paper, we propose a new approach to extract the discriminant features within a biometric image in order to use Later in a biometric identification system. Thus, qualified as universal approximator, Takagi-Sugeno fuzzy system is adopted to model the biometric images through optimization of error target function, in which, a conjugate gradient method is used to establish the proposed algorithm. In order to evaluate our method, the PolyU multispectral palmprint database is used. The obtained results show that the biometric system errors are extremely reduced especially when the Blue spectral band is used. Thus, compared with the conventional features extraction methods, our method is more secure, fast and points at increased identification accuracy which will undoubtedly can be used in high secure applications.
MULTIMODEL BIOMETRIC AUTHENTICATION BASED ON FINGER PRINT AND KEYSTROKE DYNAMICS USING FUZZY SET
Background: Biometrics is providing more security since it is used to uniquely identify individuals by their physical characteristics or personal behavior traits. Proposed approach is a multimodal biometric authentication system, since it is based on physical and behavioral characteristics. We are using keystroke dynamics as behavioral traits and used fuzzy set approach for classification. Advantage of this approach is not using the sharp cut off values of user password entry timing information instead it is using the Minimum and Maximum range values time as keystroke feature. Objective: To provide user authentication based on Keystroke dynamics by using fuzzy set approach in order to avoid unauthorized user access of the system. Results: We have used duration and latency time as keystroke features and fuzzy set approach is used for classification. By using this approach will reduce the error rate for incorrectly identifying the wrong user. Based on this approach the accuracy level will be improved.