Risk Estimation for a Secure & Usable User Authentication Mechanism for Mobile Passenger ID Devices

User Authentication in mobile devices acts as a first line of defense verifying the user's identity to allow access to the resources of a device and typically was based on 'something the user knows', known also as knowledge-based user authentication for several decades. However, recent studies point out that although knowledge-based user authentication has been the most popular for authenticating an individual, nowadays it is no more considered secure and convenient for the mobile user as it is imposing several limitations in terms of security and usability. These limitations stress the need for the development and implementation of more secure and usable user authentication methods. Toward this direction, user authentication based on the 'something the user is' has caught the attention. This category includes authentication methods which make use of human physical characteristics (also referred to as physiological biometrics), or involuntary actions (also referred to as behavioral biometrics). In particular, risk-based user authentication based on behavioral biometrics appears to have the potential to increase the reliability of authentication without sacrificing usability. In this context, we focus on the estimation of the risk score, in a continuous mode, of the risk-based user authentication mechanism that we have proposed in our previous work for mobile passenger identification (ID) devices for land/sea border control.