An adaptive approach for continuous multi-factor authentication in an identity eco-system


Multi-factor Authentication (MFA) is the current trend to genuinely identify the legitimate users in cyber eco-system through an active authentication process. This process includes passwords, security token, biometrics, human cognitive behavior metrics, etc. New sensors and better authentication modalities are evolving, which provide the opportunity for the security researchers to come up with new solutions facilitating MFA to different online resource access and identity management systems. This paper focuses on the design and development of a framework for continuous MFA where authentication modalities are selected adaptively through sensing many characteristics of the user's operating environment. The degree of adaptiveness in the selection of authentication modalities exhibits dynamism in the authentication process and lessens the burden of the users to use the same set of authentication process in less trustworthy environments. A trustworthy framework to quantify the available authentication modalities is proposed and the applicability of the framework for identity eco-system is illustrated in this paper. Copyright © 2014 ACM.

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ACM International Conference Proceeding Series