Deriving trust from experience

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Abstract

In everyday life, trust is largely built from experience. Reputation-based trust models have been developed to formalize this concept. The application to networks like the Internet where a very large number of predominantly unknown principal identities engage in interactions is appealing considering that the evaluation of trusted experience may result in a more successful choice of trusted parties to interact with. In this paper we pick the SECURE framework, as developed within the equally named EU project on Global Computing, which builds upon event structures to model possible outcomes of interactions. We extend it by three concepts: (i) a flexible way to determine a degree of trust from given past behavior, (ii) a basic notion of context, exemplarily in the form of roles the interacting parties may occupy, and (iii) we explicitly equip observed events with a time component to refine the granularity of observations. We extend definitions of concepts used in SECURE in order to incorporate our notion of context information, we provide the syntax and semantics of an LTL-like logic, in its basics similar to the one proposed by Krukow, Nielsen and Sassone, that allows for layered reasoning about context information. We then show how this new language relates to the one used in SECURE and we determine under which conditions our concept of deriving trust from experience may be used within SECURE's computational model to obtain a global state of trust. © 2010 Springer-Verlag.

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Eilers, F., & Nestmann, U. (2010). Deriving trust from experience. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5983 LNCS, pp. 36–50). https://doi.org/10.1007/978-3-642-12459-4_4

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