Uncertainty in Probabilistic Trust Models

Computational models of trust try to transfer the concept of trust from the real to the virtual world. While such models have been widely investigated in the past decade, the uncertainty involved in trust computation has been overlooked in the literature. In this paper, uncertainty of probabilistic trust models is quantified using confidence intervals and its factors are determined through simulation. The results confirm the importance and highlight the amount of uncertainty in the Beta and HMM (Hidden Markov Model) trust models. In addition, an uncertainty-driven method is proposed which reduces the risk involved in the trust-based utility maximization according to uncertainty.