Abstract
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 future 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.
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© 2005 International Federation for Information Processing
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Shi, J., v. Bochmann, G., Adams, C. (2005). A Trust Model with Statistical Foundation. In: Dimitrakos, T., Martinelli, F. (eds) Formal Aspects in Security and Trust. IFIP WCC TC1 2004. IFIP International Federation for Information Processing, vol 173. Springer, Boston, MA. https://doi.org/10.1007/0-387-24098-5_11
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DOI: https://doi.org/10.1007/0-387-24098-5_11
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