Movement Pattern Based Authentication for Smart Mobile Devices

We outline a novel method of user authentication for smart mobile devices, such as smartphones or tablets and propose movement pattern based authentication as an alternate to current methods that relies on a pin or drawn-pattern. While the current methods are vulnerable against common attacks (e.g., smudge attacks, shoulder surfing), our method, in contrast, is more resilient against the attacks of these kinds because it utilizes sensory data given off by the device during a preset movement for authentication. In our experiment, we recorded the values given off by four physical observational sensors: (1) accelerometer, (2) linear accelerometer, (3) gyroscope and (4) tilt sensor, which each had three axes, over a set of movements. We experimented with 10 arbitrary movement-patterns and gathered 12 samples of each (net 120 samples) to test with. We developed our own method of authentication, through which we performed 35,650 authentication attempts and found a 20.36% Equal Error Rate.