Touch-interaction behavior for continuous user authentication on smartphones

The increasing use of smartphones to access sensitive and privacy data has given rise to the need of secure authentication technique. Existing authentication mechanisms on smartphones can only provide one-time verification, but the verified users are still vulnerable to the session hijacking. In this article, we propose a transparent and continuous authentication system based on users' touch interaction data. We consider four common types of touch operations, and extract behavioral features to characterize users' touch behavior. Distance-measurement technique is applied to mitigate the behavioral variability. Then a multiple decision procedure is developed to perform continuous authentication, in which one-class classification algorithms are applied for classification. The efficacy of our approach is validated through a series of experiments in four real-world application scenarios. Our experimental results show that the proposed approach could verify a user in an accurate and timely manner, and suffice to be an enhancement for traditional authentication mechanisms in smartphones.