A Secured Authentication System Using an Effective Keystroke Dynamics

Abstract

In the field of computer security, most promising field is securing the data by allowing ease access to authorized users. The biometric techniques like face recognition, voice recognition and digital signatures provide good authentication security. The keystroke dynamics is defined to be a low cost, strong behavioral biometric-based authentication system, based on consistent typing rhythm patterns at a keyboard terminal, which will be individually unique. This paper exhibits an effective, efficient and robust user authentication. Authentication system is based on effective Adaptive Learning Classification (ALC) algorithm, where a self-threshold for each user was decided based on user input. Training and testing data lead to an average false reject rate of 10.00 % and the average false accept rate of 0.0025 %.