Reputation Management

About

Background The primary goals of a reputation management scheme are determining the service quality of the peers who provide a service (i.e., service providers) by using feedback from the peers who have rated the service (i.e., raters), and determining the trustworthiness of the raters by analyzing the feedback they provide about the service providers. Thus, the success of a reputation management scheme depends on the robustness of the mechanism to accurately evaluate the reputations of the service providers and the trustworthiness of the raters. As in every security system, trust and reputation management systems are subject to malicious behaviors. Malicious raters may attack particular service providers (e.g., sellers) to undermine their reputations while helping other service providers by boosting their reputations. Malicious service providers may also provide good service qualities (or sell high-quality products) to certain customers in order to keep their reputations high while cheating other customers unlikely to provide feedback. Moreover, malicious raters or service providers may collaboratively mount sophisticated attack strategies by exploiting their prior knowledge about the reputation mechanism. Hence, building a resilient trust and reputation management system that is robust against malicious activities is a challenging issue. Technology Faramarz Fekri and Arman Ayday from the School of Electrical and Computer Engineering at Georgia Tech have created the reputation management methods that can include receiving a plurality of ratings. Each rating can be associated with a service provider and a rater. The method can further include modeling the service providers, the raters, and the ratings as a factor graph representing the factorization of a joint probability distribution function of variables, calculating the marginal distributions using a belief propagation algorithm applied to the factor graph, and determining reputation values associated with the service providers and trustworthiness values associated with the raters based on the calculating.  Each factor node of the factor graph can correspond to a rater and be associated with a local function representing marginal distributions of a subset of the variables. The subset of variables can include a trustworthiness value associated with the rater and one or more ratings associated with the rater. Each variable node of the factor graph can correspond to a service provider and each service provider can be associated with a reputation value.