Shuo Zhao
ABSTRACT
Identity authentication plays an important role in maintaining social security. With the rapid growth of population, an important issue is put in front of people. How to identify people more accurately and faster? This paper presents a novel behavioral biometric authentication mechanism for smartphones, named PickupAuth. PickupAuth relies on a combined movement, which is the user picks up the phone to his chest and clicks on the touch screen. PickupAuth uses the built-in smartphone sensors to collect the force of the click screen, the acceleration data, the magnetic field data, and the rotation rate. A new proposed feature subset selection algorithm based on the correlation and weight values and Random Forest classification algorithm are used to analyze the sensor data. Experiments on 110 identity users show that the accuracy reaches 98.44% in sitting posture and 97.46% in standing posture. Besides, PickupAuth is more efficient than state of the art considering the training data acquisition time and the training time.
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Index Terms
- A Novel Smartphone Identity Authentication Mechanism
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