Enhanced User Authentication Through Trajectory Clustering
Password authentication is the most commonly used technique to authenticate the user validity. However, due to its simplicity, it is vulnerable to pseudo attacks. It can be enhanced using various biometric techniques such as thumb impression, finger movement, eye movement etc. In this paper, the authors concentrate on the most economic technique, based on the user habitual rhythm pattern i.e. not what they type but how they type is the measure for authenticating the user. They consider the latency between key events as the trajectory, and trajectory clustering is used to obtain the hidden patterns of the user. Obtained pattern can be considered as a cluster of measurements that can be used to differentiate from other users.