SilentSense: Silent User Identification via Dynamics of Touch and Movement Behavioral Biometrics.

摘要: With the increased popularity of smartphones, various security threats and privacy leakages targeting them are discovered investigated. In this work, we present \ourprotocoltight, a framework to authenticate users silently transparently by exploiting dynamics mined from user touch behavior biometrics micro-movement device caused user's screen-touch actions. We build "touch-based biometrics" model owner extracting some principle features, then verify whether current is or guest/attacker. When using smartphone, unique operating detected learnt collecting sensor data events silently. mobile, mobile devices suppressed that due large scale user-movement which will render touch-based ineffective. To address this, integrate movement-based for each with previous biometrics. conduct extensive evaluations our approaches on Android show identification accuracy over 99%.