Abstract.Trust is an important tool in human life, as it enables people to cope with the uncertainty caused by the free will of others. Uncertainty and uncontrollability are also issues in computer-assisted collaboration and electronic commerce in particular. A computational model of trust and its implementation can alleviate this problem.This survey is directed to an audience wishing to familiarize themselves with the field, for example to locate a research target or implement a trust management system. It concentrates on providing a general overview of the state of the art, combined with examples of things to take into consideration both when modelling trust in general and building a solution for a certain phase in trust management, be it trust relationship initialization, updating trust based on experience or determining what trust should have an effect on.

Electronic markets, distributed peer-to-peer applications and other forms of online collaboration are all based on mutual trust, which enables transacting peers to overcome the uncertainty and risk inherent in the environment. Reputation systems provide essential input for computational trust as predictions on future behaviour based on the past actions of a peer. In order to analyze the maturity of current reputation systems, we compare eleven reputation systems within a taxonomy of the credibility aspects of a reputation system. The taxonomy covers three topics: 1) the creation and content of a recommendation, 2) the selection and use of recommenders, and 3) the interpretation and reasoning applied to the gathered information. Although we find it possible to form a trusted reputation management network over an open network environment, there are still many regulatory and technical obstacles to address. This survey reveals various good mechanisms and methods used, but the area still requires both a) formation of standard mechanisms and metrics for reputation system collaboration and b) standard metainformation of right granularity for evaluating the credibility of reputation information provided.

The increasing pressure for enterprises to join into agile business networks is changing the requirements on the enterprise computing systems. The supporting infrastructure is increasingly required to provide common facilities and societal infrastructure services to support the lifecycle of loosely-coupled, eContract-governed business networks. The required facilities include selection of those autonomously administered business services that the enterprises are prepared to provide and use, contract negotiations, and furthermore, monitoring of the contracted behaviour with potential for breach management. The essential change is in the requirement of a clear mapping between business-level concepts and the automation support for them. Our work has focused on developing B2B middleware to address the above challenges; however, the architecture is not feasible without management facilities for trust-aware decisions for entering business networks and interacting within them. This paper discusses how trust-based decisions are supported and positioned in the B2B middleware.

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Abstract-Enterprise computing is moving towards more open, collaborative systems. Joining a business network must be made efficient, despite the technical and semantic interoperability challenges involved in connecting different information and communication systems. Trust or lack thereof forms a pragmatic challenge: partners must continuously evaluate whether they trust each other enough to collaborate in the face of risk. Supporting technology is needed for making trust-based decisions on routine business transactions and observing the business peers for malicious or incorrect behaviour on interactions. We present a trust model for automating routine decision-making which considers both risk probabilities and tolerance valuations in the enterprise, and is dynamically updated based on new experience gathered both locally and from third parties.

This paper is available online at www.jtaer.com DOI: 10.4067/S0718-1876201000020000

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