Combining keystroke and mouse dynamics for continuous user authentication and identification

In this paper, we analyze the performance of a continuous user authentication and identification system for a PC under various analysis techniques. We applied a novel identification technique called Pairwise User Coupling (PUC) on our own dataset for the analysis. This dataset is a combination of keystroke and mouse usage behaviour data. We obtained an identification accuracy of 62.2% for a closed-set experiment, where the system needs on average of 471 actions to detect an impostor. In case of an open-set experiment the Detection and Identification Rate (DIR) of 58.9% was obtained, where the system needs on average of 333 actions to detect an impostor.