Title: Continuous Implicit Authentication for Mobile Devices based on Adaptive Neuro-Fuzzy Inference System,
Abstract: As mobile devices have become indispensable in modern life, mobile security
is becoming much more important. Traditional password or PIN-like
point-of-entry security measures score low on usability and are vulnerable to
brute force and other types of attacks. In order to improve mobile security, an
adaptive neuro-fuzzy inference system(ANFIS)-based implicit authentication
system is proposed in this paper to provide authentication in a continuous and
transparent manner.To illustrate the applicability and capability of ANFIS in
our implicit authentication system, experiments were conducted on behavioural
data collected for up to 12 weeks from different Android users. The ability of
the ANFIS-based system to detect an adversary is also tested with scenarios
involving an attacker with varying levels of knowledge. The results demonstrate
that ANFIS is a feasible and efficient approach for implicit authentication
with an average of 95% user recognition rate. Moreover, the use of ANFIS-based
system for implicit authentication significantly reduces manual tuning and
configuration tasks due to its selflearning capability.