Abstract. Evidence based trust management, where automated decision making is supported through collection of evidence about the trustworthiness of entities from a variety of sources, has gained popularity in recent years. So far work in this area has primarily focussed on schemes for combining evidence from potentially unreliable sources (recommenders) with the aim of improving the quality of decision making. The large body of literature on reputation systems is testament to this. At the same time, little consideration has been given to the actual gathering of useful and detailed experiential evidence. Most proposed systems use quite simplistic representations for experiences, and mechanisms where high level feedback is provided by users. Consequently, these systems provide limited support for automated decision making. In this paper we build upon our previous work in trust-based interaction modelling and we present an interaction monitor that enables automated collection of detailed interaction evidence. The monitor is a prototype implementation of our generic interaction monitoring architecture that combines well understood rule engine and event management technology. This paper also describes a distributed file server scenario, in order to demonstrate our interaction model and monitor. Finally, the paper presents some preliminary results of a simulation-based evaluation of our monitor in the context of the distributed file server scenario.
English and Terzis presented an interaction monitor that enables automated collection of detailed interaction evidence based on interaction modeling REF .
Gathering Experience in Trust-based Interactions
iTrust
Computer Science