  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.
