网络与信息安全学报 (Oct 2022)
Novel continuous identity authentication method based on mouse behavior
Abstract
With the rapid development of Internet technologies, security issues have always been the hot topics.Continuous identity authentication based on mouse behavior plays a crucial role in protecting computer systems, but there are still some problems to be solved.Aiming at the problems of low authentication accuracy and long authentication latency in mouse behavior authentication method, a new continuous identity authentication method based on mouse behavior was proposed.The method divided the user’s mouse event sequence into corresponding mouse behaviors according to different types, and mined mouse behavior characteristics from various aspects based on mouse behaviors.Thereby, the differences in mouse behavior of different users can be better represented, and the authentication accuracy can be improved.Besides, the importance of mouse behavior features was obtained by the ReliefF algorithm, and on this basis, the irrelevant or redundant features of mouse behavior were removed by combining the neighborhood rough set to reduce model complexity and modeling time.Moreover binary classification was adopted.The algorithm performed the training of the authentication model.During identity authentication, the authentication model was used to obtain a classification score based on the mouse behavior collected each time, and then the user’s trust value was updated in combination with the trust model.When the user’s trust value fell below the threshold of the trust model, it might be judged as illegal user.The authentication effect of the proposed method was simulated on the Balabit and DFL datasets.The results show that, compared with the methods in other literatures, this method not only improves the authentication accuracy and reduces the authentication latency, but also has a certain robustness to the illegal intrusion of external users.
