Article ID Journal Published Year Pages File Type
6884591 Journal of Information Security and Applications 2018 13 Pages PDF
Abstract
Multi-modal active authentication schemes fuse decisions of multiple behavioral biometrics (behaviometrics) to reduce identity verification errors. The challenge that we address in this work is the security risk caused by these decision fusion schemes making invalid assumptions, such as a fixed probability of (in)correct recognition and a temporal congruence of behaviometrics. To mitigate this risk, this paper presents a formal trust model that drives the behaviometric selection and composition. Our trust model adopts a hybrid approach combining policy and reputation based knowledge representation techniques. Our model and framework (1) externalizes trust knowledge from the authentication logic to achieve loosely coupled trust management, and (2) formalizes this knowledge in description logic to reason upon and broker complex distributed trust relationships to make risk-adaptive decisions for multi-modal authentication. The evaluation of our proof-of-concept illustrates an acceptable performance overhead while lifting the burden of manual trust and behaviometric management for multi-modal authentication.
Related Topics
Physical Sciences and Engineering Computer Science Computer Networks and Communications
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