Hijacked Smart Devices - Methodical Foundations for Autonomous Theft Awareness based on Activity Recognition and Novelty Detection

摘要

Personal devices such as smart phones are increasingly utilised in everyday life. Frequently, Activity Recognition is performed on these devices to estimate the current user status and trigger automated actions according to the user's needs. In this article, we focus on improving the self-awareness of such systems in terms of detecting theft: We equip devices with the capabilities to model their own user and to, e.g., alarm the legal user if an unexpected other person is carrying the device. We gathered 24hours of data in a case study with 14 persons using a Nokia N97 and trained an activity recognition system. Based on it, we developed and investigated an autonomous novelty detection system that continuously checks if the observed user behavior corresponds to the initial model, and that gives an alarm if not. Our evaluations show that the presented method is highly successful with a successful theft detection rate of over 85% for the trained set of persons. Comparison experiments with state of the art techniques support the strong practicality of our approach.