Matrix analysis
A Computational Model of Trust and Reputation for E-businesses
HICSS '02 Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02)-Volume 7 - Volume 7
PeerTrust: Supporting Reputation-Based Trust for Peer-to-Peer Electronic Communities
IEEE Transactions on Knowledge and Data Engineering
TRAVOS: Trust and Reputation in the Context of Inaccurate Information Sources
Autonomous Agents and Multi-Agent Systems
A Bayesian Model for Event-based Trust
Electronic Notes in Theoretical Computer Science (ENTCS)
ARES '07 Proceedings of the The Second International Conference on Availability, Reliability and Security
Using Trust for Secure Collaboration in Uncertain Environments
IEEE Pervasive Computing
Towards a formal framework for computational trust
FMCO'06 Proceedings of the 5th international conference on Formal methods for components and objects
CONCUR'10 Proceedings of the 21st international conference on Concurrency theory
Trust-based minimum cost opportunistic routing for Ad hoc networks
Journal of Systems and Software
FAST'09 Proceedings of the 6th international conference on Formal Aspects in Security and Trust
Hi-index | 5.23 |
Research in models for experience-based trust management has either ignored the problem of modelling and reasoning about dynamically changing principal behaviour, or provided ad hoc solutions to it. Probability theory provides a foundation for addressing this and many other issues in a rigorous and mathematically sound manner. Using Hidden Markov Models to represent principal behaviours, we focus on computational trust frameworks based on the 'beta' probability distribution and the principle of exponential decay, and derive a precise analytical formula for the estimation error they induce. This allows potential adopters of beta-based computational trust frameworks and algorithms to better understand the implications of their choice.