Affiliation:
1. University of Waterloo, Waterloo, Canada
2. University of Guelph, Guelph, Canada
Abstract
Adaptive authentication enables smartphones and enterprise apps to decide when and how to authenticate users based on contextual and behavioral factors. In practice, a system may employ multiple policies to adapt its authentication mechanisms and access controls to various scenarios. However, existing approaches suffer from contradictory or insecure adaptations, which may enable attackers to bypass the authentication system. Besides, most existing approaches are inflexible and do not provide desirable access controls. We design and build a multi-stage risk-aware adaptive authentication and access control framework (MRAAC), which provides the following novel contributions:
Multi-stage:
MRAAC organizes adaptation policies in multiple stages to handle different risk types and progressively adapts authentication mechanisms based on context, resource sensitivity, and user authenticity.
Appropriate access control:
MRAAC provides libraries to enable sensitive apps to manage the availability of their in-app resources based on MRAAC’s risk awareness.
Extensible:
While existing proposals are tailored to cater to a single use case, MRAAC supports a variety of use cases with custom risk models. We exemplify these advantages of MRAAC by deploying it for three use cases: an enhanced version of Android Smart Lock, guest-aware continuous authentication, and corporate app for BYOD. We conduct experiments to quantify the CPU, memory, latency, and battery performance of MRAAC. Our evaluation shows that MRAAC enables various stakeholders (device manufacturers, enterprise and secure app developers) to provide complex adaptive authentication workflows on COTS Android with low processing and battery overhead.
Funder
Waterloo-Huawei Joint Innovation Laboratory
Publisher
Association for Computing Machinery (ACM)
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