Multi-touch Authentication Using Hand Geometry and Behavioral Information

In this paper we present a simple and reliable authentication method for mobile devices equipped with multi-touch screens such as smart phones, tablets and laptops. Users are authenticated by performing specially designed multi-touch gestures with one swipe on the touchscreen. During this process, both hand geometry and behavioral characteristics are recorded in the multi-touch traces and used for authentication. By combining both geometry information and behavioral characteristics, we overcome the problem of behavioral variability plaguing many behavior based authentication techniques – which often leads to less accurate authentication or poor user experience – while also ensuring the discernibility of different users with possibly similar handshapes. We evaluate the design of the proposed authentication method thoroughly using a large multi-touch dataset collected from 161 subjects with an elaborately designed procedure to capture behavior variability. The results demonstrate that the fusion of behavioral information with hand geometry features produces effective resistance to behavioral variability over time while at the same time retains discernibility. Our approach achieves EER of 5.84% with only 5 training samples and the performance is further improved to EER of 1.88% with enough training. Security analyses are also conducted to demonstrate that the proposed method is resilient against common smartphone authentication threats such as smudge attack, shoulder surfing attack and statistical attack. Finally, user acceptance of the method is illustrated via a usability study.