Modeling multimodal biometric modalities for continuous user authentication
Continuous authentication offers the ability to continuously verify users' identity for accessing to the protected resource. Although current explorations such as face and fingerprint verification have seen varying rates of success, three main problems may limit their applicability in the context of information protection and access control: they can be of low availability in some practical scenarios, they can be intrusive, and they commonly require costly equipment. This paper presents a multimodal biometrics authentication system that can continuously verify the presence of a logged in user. Three passive biometric modalities are currently used keystroke (i.e. behavioral biometric) face (i.e. physiological biometric) and skin color (i.e. soft biometric) but our approach can also be readily extended to include more modalities. By fusing these three passive biometrics, the continuous authentication system combines both temporal and modality information holistically, and can keep verifying who is using the computing system, without troubling users' routine activities. Based on real data resulting from our implementation, we find the results to be very promising with a false acceptance rate of 0% and a false rejection rate of 0.72% Additional experiment on the size of observation window is provided to further examine the applicability of the proposed approach.
2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)