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
Review on Computational Trust and Reputation Models
Artificial Intelligence Review
Coping with inaccurate reputation sources: experimental analysis of a probabilistic trust model
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Using Trust for Secure Collaboration in Uncertain Environments
IEEE Pervasive Computing
P2P reputation management: Probabilistic estimation vs. social networks
Computer Networks: The International Journal of Computer and Telecommunications Networking - Management in peer-to-peer systems
Socio-technical defense against voice spamming
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Foundations of security analysis and design IV
Non-cryptographic methods for improving real time transmission security and integrity
Annales UMCS, Informatica - Security Systems
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Since the millennium, a quickly increasing number of research papers in the field of "computational trust and reputation" have appeared in the Computer Science literature. However, it remains hard to compare and evaluate the respective merits of proposed systems. We argue that rigorous use of formal probabilistic models enables the clear specification of the assumptions and objectives of systems, which is necessary for comparisons. To exemplify such probabilistic modeling, we present a simple probabilistic trust model in which the system assumptions as well as its objectives are clearly specified. We show how to compute (in this model) the so-called predictive probability: The probability that the next interaction with a specific principal will have a specific outcome. We sketch preliminary ideas and first theorems indicating how the use of probabilistic models could enable us to quantitatively compare proposed systems in various different environments.