| dc.description.abstract | Online communities provide a unique environment where interactions performed among its subscribers who have shared interest. Members of these virtual communities are typically classified as trustworthy and untrustworthy. Trust and reputation became indispensable properties due to the rapid growth of uncertainty and risk. This risk is a result of cyber-attacks carried out by untrustworthy actors. A malicious attack may produce misleading information making the community unreliable. Trust mechanism is a substantial instrument for empowering safe functioning within a community. Most virtual communities are centralized, which implies that they own, manage, and control trust information without given permission from the legitimate owner. The problem of ownership arises as actors may lose their reputations if the community decided to shut down its business. Sharing information is another valuable feature that aids lessening the impact of dishonest behavior.
A new trust model called “TrustMe” was developed in this research as a reliable mechanism that generates precise trust information for virtual communities. TrustMe consists of several factors that aim to confuse untrustworthy actors, and to make the generated trust score is hardly reversed. A blockchain-based trust model is also developed to address the problem of ownership as well as offering a decentralized information sharing mechanism through a distributed application called “DATTC.” The efficiency of the proposed models was identified by conducting various analytic experimental studies. An unsupervised machine learning method (density-based clustering) was applied using two different datasets. Also, graph analysis was conducted to study the evolvement of communities and trust by finding connections between graph metrics and trust scores generated by TrustMe. Finally, a set of simulations using stochastic models to evaluate the accuracy and success rates of TrustMe, and a simulation set mimicked the blockchain-model in alleviating the influence of Sybil attack. The relationships among actors were hypothesized as actors divided into trustworthy and untrustworthy performing cooperative and malicious attacks. The results of the study prove that TrustMe can be promising and support the first hypothesis as TrustMe outperformed other trust models. Additionally, the results confirm that the blockchain-based trust model efficiently mitigates malicious cyber-attack by employing cross-community trust and preserves ownership property. | en_US |
