Fuzzy aproach in biometric authentication by keystroke dynamics (original) (raw)
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.
Fuzzy and Markov models for keystroke biometrics authentication
Proceedings of the 7th WSEAS …, 2007
Keystroke biometrics authentication system is based on a password and keystroke biometric features captured when a user is typing in the password. The system offers a higher level of security and convenience for computers. The system does not require additional hardware as it can be used with any existing keyboard, making it relatively inexpensive and fairly unobtrusive to the user. There have been existing research publications on keystroke biometrics authentication that have solved problems in selecting appropriate keystroke features and modeling users. However methods for calculating score to reduce authentication error are not taken into account. Therefore we propose to use Markov modeling and fuzzy set theory-based normalization methods for keystroke biometrics authentication that can reduce both false rejection and false acceptance rates. Experiments showed better performance for the proposed methods.
Biometric Authentication Based on Keystroke Dynamics for Realistic User
User authentication is to prevent the unauthorized access based on username and password, but it has less security because of the possibilities of hackers can easily stolen the password of the legitimate users. Biometric technologies are providing more security since they provide more reliable and efficient means of authentication and verification. We present a novel approach for user authentication based on fingerprint and the keystrokedynamics of the password entry. The authentication process is done via 3 ways. 1) Login credential based on Username and password; 2) Finger print; 3) Keystroke Dynamics (patterns of rhythm and timing created when person types via keyboard).Proposed approach is a multimodal biometric authentication system. Index Terms – Biometric technology, finger print, keystroke dynamics, user authentication, multimodal biometric authentication I.INTRODUCTION The first and foremost step in preventing unauthorized access is user Authentication. User authentication ...
2019
The global access of information and resources from anywhere has increased the chance of intrusion and hacking of confidential data. Username with password is the commonly used authentication mechanism which is used for almost all online applications from net banking to online examinations. However, advanced safeguard mechanisms are sought against unauthorized access as the passwords can be hacked easily. To strengthen the password, it can be combined with biometric technology. Keystroke biometrics, a strong behavioral biometric, can be considered as a secure method compared to other methods even if the imposter knows the username and password as it is based on user habitual typing rhythm patterns. For any online application the accuracy level plays a vital role. But the accuracy of keystroke authentication when compared with other biometric authentication mechanisms is low. To improve the accuracy and minimize the training and testing time, this chapter proposes a wrapper-based cla...
Keystroke Dynamics for Authentication Based on Biometrics for Convincing User
User authentication is to prevent the unauthorized access based on username and password, but it has less security because of the possibilities of hackers can easily stolen the password of the legitimate users. Biometric technologies are providing more security since they provide more reliable and efficient means of authentication and verification. We present a novel approach for user authentication based on fingerprint and the keystroke dynamics of the password entry. The authentication process is done via 3 ways. 1) Login credential based on Username and password; 2) Finger print; 3) Keystroke Dynamics (patterns of rhythm and timing created when person types via keyboard).Proposed approach is a multimodal biometric authentication system.
Continuous keystroke dynamics: A different perspective towards biometric evaluation
Information Security Technical Report, 2012
In this paper we will describe a way to evaluate a biometric continuous keystroke dynamics system. Such a system will continuously monitor the typing behaviour of a user and will determine if the current user is still the genuine one or not, so that the system can be locked if a different user is detected. The main focus of this paper will be the way to evaluate the performance of such a biometric authentication system. The purpose of a performance evaluation for a static and for a continuous biometric authentication system differ greatly. For a static biometric system it is important to know how often a wrong decision is made. On the other hand, the purpose of a performance evaluation for a continuous biometric authentication system is not to see if an impostor is detected, but how fast he is detected. The performance of a continuous keystroke dynamic system will be tested based on this new evaluation method. ª
Biometric patterns recognition using keystroke dynamics
2018
This paper aims to describe a strategy for biometric authentication embedded system that uses keystroke dynamics to recognize the users. The main motivation of this work is a gap identified on the biometric authentication devices market that demonstrates the lack of a low cost and high efficiency product. Therefore, the use of low cost microcontrollers coupled with a good biometric authentication strategy could fill this gap. The PIC and ESP microcontrollers were used to create a prototype with the purpose of performing measurements and generating users’ biometric models. During these measurements 9 volunteers had their typing characteristics extracted and stored. After data collection, several tests were performed and values of 36% for FRR and 7.2% for FAR were found. More expensive results can still be achieved by modifying some punctualities in data collection, as commented at the end of the paper.
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.
Fuzzy evaluation of biometric authentication systems
Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems, 2011
This paper presents a new approach in evaluation of biometric identity verification system, which is based on three important indicators: false acceptance rate, false reject rate and failure to enroll rate. Those mentioned indicators are grouped by using fuzzy sets and linguistic variables to provide important pieces of information.
Journal of Modern Physics, 2018
This paper presents the formulation of the possibilistic Renyi entropy function from the Renyi entropy function using the framework of Hanman-Anirban entropy function. The new entropy function is used to derive the information set features from keystroke dynamics for the authentication of users. A new composite fuzzy classifier is also proposed based on Mamta-Hanman entropy function and applied on the Information Set based features. A comparison of the results of the proposed approach with those of Support Vector Machine and Random Forest classifier shows that the new classifier outperforms the other two.