Security Enhancement of Knowledge-based User Authentication through Keystroke Dynamics

Abstract

Keystroke Dynamics is a behavioural biometrics characteristic in Biometric science, which solve the issues in user identification or verification. In Knowledge-based user authentication technique, we compromise with PIN or password which is unsafe due to different type of attacks. It is good to choose password with the combination of upper and lower case letter with some digits and symbols, but which is very hard to remember or generally we forget to distinguish those passwords for different access control systems. Our system not only takes the users' entered texts but their typing style is also account for. In our experiment, we have not taken hard password type texts, we have chosen some daily used words where users are habituated and comfortable at typing and we obtained the consisting typing pattern. Different distance-based and data mining algorithms we have applied on collected typing pattern and obtained impressive results. As per our experiment, if we use keystroke dynamics in existing knowledge based user authentication system with minimum of five daily used common texts then it increases the security level up to 97.6% to 98.2% (if we remove some of the irrelevant feature sets).