Detecting and Reacting to Changes in Reputation Flows
Abstract
In inter-enterprise collaboration, autonomic services from different organizations must independently determine which other services they can rely on. Reputation-based trust management in the Pilarcos open service ecosystem combines shared experience information on the actors’ past behaviour and the decision context to estimate the risks of a collaboration. The trust decision process is semi-automatic, with selected decisions forwarded to a human user. A particularly interesting feature of the decision process is incongruity, that is, unexpected changes in service performance. In the classical example, a previously well-behaved service turns malicious to cash in its good reputation as ill-gained monetary profit. If the reputation system swiftly reacts to such changes, it protects its user more efficiently and deters misbehaviour. We present a new model for detecting and reacting to incongruities in a reputation-based trust management system. The model is based on the concept of reputation epochs, dividing an actor’s reputation into periods of internally consistent behaviour. In contrast to earlier approaches, this model provides the necessary flexibility for the trust management system to adjust to constantly changing business situations.
Domains
Computer Science [cs]Origin | Files produced by the author(s) |
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