TY  - GEN
EP  - 312
TI  - B-Trust: Bayesian trust framework for pervasive computing
A1  - Quercia, D.
A1  - Hailes, S.
A1  - Capra, L.
ID  - discovery4884
UR  - http://dx.doi.org/doi:10.1007/11755593_22
T3  - Lecture Notes in Computer Science
CY  - Berlin / Heidelberg, Germany
N1  - The original publication is available at www.springerlink.com
AV  - public
PB  - Springer Verlag
N2  - 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.
SN  - 3540342953
SP  - 298
Y1  - 2006/08//
ER  -