Fuzzy Logic-based Implicit Authentication for Mobile Access Control
This work addresses privacy protection for mobile device users by providing a lightweight, real-time authentication method, though it appears incremental as it builds on existing fuzzy logic techniques.
The authors tackled the problem of user privacy compromise on mobile devices by proposing a fuzzy logic-based implicit authentication scheme that operates adaptively in the background, achieving high system accuracy and timely detection of abnormal activity based on real data from Android users over several weeks.
In order to address the increasing compromise of user privacy on mobile devices, a Fuzzy Logic based implicit authentication scheme is proposed in this paper. The proposed scheme computes an aggregate score based on selected features and a threshold in real-time based on current and historic data depicting user routine. The tuned fuzzy system is then applied to the aggregated score and the threshold to determine the trust level of the current user. The proposed fuzzy-integrated implicit authentication scheme is designed to: operate adaptively and completely in the background, require minimal training period, enable high system accuracy while provide timely detection of abnormal activity. In this paper, we explore Fuzzy Logic based authentication in depth. Gaussian and triangle-based membership functions are investigated and compared using real data over several weeks from different Android phone users. The presented results show that our proposed Fuzzy Logic approach is a highly effective, and viable scheme for lightweight real-time implicit authentication on mobile devices.