CASA: Context-Aware Scalable Authentication

Abstract

We introduce context-aware scalable authentication (CASA) as a way of balancing security and usability for authentication. Our core idea is to choose an appropriate form of active authentication (e.g., typing a PIN) based on the combination of multiple passive factors (e.g., a user's current location) for authentication. We provide a probabilistic framework for dynamically selecting an active authentication scheme that satisfies a specified security requirement given passive factors. We also present the results of three user studies evaluating the feasibility and users' receptiveness of our concept. Our results suggest that location data has good potential as a passive factor, and that users can reduce up to 68% of active authentications when using an implementation of CASA, compared to always using fixed active authentication. Furthermore, our participants, including those who do not using any security mechanisms on their phones, were very positive about CASA and amenable to using it on their phones.