Applying empirical thresholding algorithm for a keystroke dynamics based authentication system

• Main Authors: Venugopal, Priya Chaliyath, Viji, Kamalan Saroja Angel
• Format: Article
• Language: English
• Published: Universiti Utara Malaysia Press 2019
• Subjects: QA76 Computer software
• Online Access: http://repo.uum.edu.my/26843/1/JICT%2018%204%202019%20383-413.pdf; http://repo.uum.edu.my/26843/; http://jict.uum.edu.my/index.php/previous-issues/168-journal-of-information-and-communication-technology-jict-vol-18-no-4-october-2019

Through the application of a password-based authentication technique, users are granted permission to access a secure system when the username and password matches with that logged in database of the system. Furthermore, anyone who provides the correct username and password of a valid user will be able to log in to the secure network. In current circumstances, impostors can hack the system to obtain a user’s password, while it has also been easy to find out a person’s private password. Thus, the existing structure is exceptionally flawed. One way to strengthen the password-based authentication technique, is by keystroke dynamics. In the proposed keystroke dynamics based authentication system, despite the password match, the similarity between the typing pattern of the typed password and password samples in the training database are verified. The timing features of the user’s keystroke dynamics are collected to calculate the threshold values. In this paper, a novel algorithm is proposed to authenticate the legal users based on the empirical threshold values. The first step involves the extraction of timing features from the typed password samples. The password training database for each user is constructed using the extracted features. Moreover, the empirical threshold limits are calculated from the timing features in the database. The second step involves user authentication by applying these threshold values. The experimental analyses are carried out in MATLAB simulation, and the results indicate a significant reduction in false rejection rate and false acceptance rate. The proposed methodology yields very low equal error rate of 0.5% and the authentication accuracy of 99.5%, which are considered suitable and efficient for real-time implementation. The proposed method can be a useful resource for identifying illegal invasion and is valuable in securing the system as a correlative or substitute form of client validation.