User identity verification via mouse dynamics

Computers and services such as eBanks and WebMails that identify users only at login via credentials are vulnerable to Identity Theft. Hackers perpetrate fraudulent activity under stolen identities by using credentials, such as passwords and smartcards, unlawfully obtained from legitimate users or by using logged-on computers that are left unattended. User verification methods provide an additional security layer by continuously confirming the identity of logged-on users based on their physiological and behavioral characteristics. We introduce a novel method that continuously verifies users according to characteristics of their interaction with the pointing device of the computer e.g. mouse, touch pad and stylus. The contribution of this work is three-fold: first, user verification is derived by combining the classification results of each individual mouse action, in contrast to the histogram approach in [2] in which verification is based on aggregations of mouse actions. Second, we propose a hierarchy of mouse actions from which the features are extracted. Third, we introduce new features to characterize the mouse activity which are used in conjunction with features proposed in previous work. The proposed algorithm outperforms current state-of-the-art methods by achieving higher verification accuracy while reducing the response time of the system.