The widespread use of the Internet signals the need for a better understanding of trust as a basis for secure on-line interaction. In the face of increasing uncertainty and risk, users and machines must be allowed to reason effectively about the trustworthiness of other entities. In this paper, we propose a trust model that assists users and machines with decision-making in online interactions by using past behavior as a predictor of likely füture behavior. We develop a general method to automatically compute trust based on self-experience and the recommendations of others. Furthermore, we apply our trust model to several utility models to increase the accuracy of decision-making in different contexts of Web Services. © 2005 by International Federation for Information Processing.
CITATION STYLE
Shi, J., Bochmann, G. V., & Adams, C. (2005). A trust model with statistical foundation. In IFIP Advances in Information and Communication Technology (Vol. 173, pp. 145–158). Springer New York LLC. https://doi.org/10.1007/0-387-24098-5_11
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