Identity Detection of Typist relying on Image Processing Techniques
Tanya Ismail Hama Amin, Armin Saeb, Hutheifa Anwar Mohammed · 2007
Global access to information and resources is becoming an essential part of nearly every aspect of our lives. Unfortunately, with this global network access comes increased chances of malicious attack and intrusion. In an effort to confront the new threats unveiled by the networking revolution of the past few years reliable, and rapid means for automatically recognizing the identity of individuals are now being sought. In this paper we consider the problem of identifying a user typing on a computer keyboard, through identification of his behavioral typing patterns and the time series consisting of keyboard events. A graphical representation of the user typing behavior in which frequency domain filtering operations are developed to robustly extract useful highlevel information from the user's behavioral images, then using cross-correlation as measure of similarity we can accurately authenticate users. Our solution is based on simple template matching methodology. Application of our results could be a second-layer behaviometric security system continually testing the current user without interfering with this user’s work while attempting to identify masquerading users. We study the effectiveness of our method over a real dataset consisting of 17 users and 23 attackers.