Role-and relationship-based identity management for privacy-enhanced E-Iearning
International Journal of Artificial Intelligence in Education
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This research explores a new model for facilitating trust in online e-learning activities. We begin by protecting the privacy of learners through identity management (IM), where personal information can be protected through some degree of participant anonymity or pseudonymity. In order to expect learners to trust other pseudonymous participants, we realize that a reliable mechanism is needed for managing participants' reputations and assuring that such reputations are legitimately obtained. Further, because participants can hold multiple identities or can adopt new pseudonymous personas, a reliable and trustworthy mechanism for reputation transfer (RT) from one persona to another is required. Such a reputation transfer model must preserve privacy and at the same time prevent linkability of learners' identities and personas. In this paper, we present a privacy-preserving reputation management (RM) system which allows secure transfer of reputation. A prototypical implementation of our reputation transfer protocol and the successful experimental deployment of our reputation management solution in an e-learning discussion forum serve as a proof of concept.