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

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