Active Linguistic Authentication Revisited - Real-Time Stylometric Evaluation towards Multi-Modal Decision Fusion

Active authentication is the process of continuously verifying a user based on his/her ongoing interaction with the computer. Forensic stylometry is the study of linguistic style, applied to author (user) identification. We evaluate the Active Linguistic Authentication Dataset [Juola et al., 2013], collected from users working individually in an office environment for a period of one week. We consider a battery of stylometric modalities, as a representative collection of high-level behavioral biometrics. As opposed to the initial evaluation presented on this dataset before on 14 users, we consider the fully collected dataset, which consists of data by 67 users. An additional significant difference is in the type of evaluation: instead of a day-based, or data-based (numberof-characters) windows considered for classification, we evaluate time-based, overlapping sliding windows; our evaluation tests the ability to produce authentication decisions every 10– 60 seconds, highly applicable to real-world active security systems. We evaluate the different sensors via cross-validation, measuring false acceptance and rejection rates (FAR & FRR). We show that under these realistic settings, stylometric sensors perform with considerable effectiveness down to 0/0.5 FAR/FRR, for decisions produced every 60 seconds, available 95% of the time. This work is considered towards a decision-fusion approach, that undertakes multiple modalities (e.g. keyboard and mouse dynamics) for making centralized, highly accurate authentication decisions.