Reputation Systems: A framework for attacks and frauds classification

Reputation and recommending systems have been widely used in e-commerce, as well online collaborative networks, P2P networks many other contexts, order to provide trust the participants involved interaction. Based on a reputation score, e-commerce user feels sense of security, leading person or not when buying selling. However, these may give false security due their gaps. This article discusses limitations current terms models determine score users. We intend contribute knowledge this field by providing systematic overview main types attack fraud found those systems, proposing novel framework classification based matrix attributes. believe such could help analyse new attacks fraud. Our work was literature review methodology.