B-trust: Bayesian Trust Framework for Pervasive Computing
Daniele Quercia, Stephen Hailes, Licia Capra

Abstract

Without trust, pervasive devices cannot collaborate effectively, and without collaboration, the pervasive computing vision cannot be made a reality. 
Distributed trust frameworks may support trust and thus foster collaboration in an hostile pervasive computing environment. 
Existing frameworks deal with foundational properties of computational trust. We here propose a distributed trust framework that satisfies a broader range of properties. 
Our framework: 
(i) evolves trust based on a Bayesian formalization, whose trust metric is expressive, yet tractable;
(ii) is lightweight; 
(iii) protects user anonymity, whilst being resistant to “Sybil attacks” (and enhancing detection of two collusion attacks); (iv) integrates a risk-aware decision module. 
We evaluate the framework through four experiments.