Multi agent system-based dynamic trust calculation model and credit management mechanism of online trading. Issue 4 (1st October 2016) - Jiang, W. J.; Xu, Y. S.; Guo, H.; Wang, C. C.; Zhang, L. M.
Abstract: Now all kinds of malicious acts appear in C2C online auctions, particularly the phenomenon of trust lack and credit fraud is very outstanding. Therefore, how to build an effective trust model has become a burning problem. Based on analyzing limitations of the existing online trust transaction mechanism, and according to characteristics (such as dynamic, innominate and suppositional) of online transaction trust problem, the article proposes a dynamic trust calculation model and reputation management mechanism of online trading based on multi-Agent system. The model consists of three parts. The first part is the trust of user domain, to put importance on the influence on current trust by recent credibility status, to motivate users to adopt an agreed cooperative strategy. The second part is the weighted average of reputation feedback score. The weighted part mainly considers the trust from the reputation feedback score person (the credibility of the feedback score), the value of the transaction (to prevent the "credit squeeze"), temporal discounted ("guard against the fluctuations of the credibility" ) and other factors. The third part is to give a weighting on the community contribution, according to the action taken by a user to the other members of the community in a time domain, to increase or decrease the user's trust to isolate the feedback submission of the credibility and punish the fraud. The paper builds the fraud limitation mechanism, which combines the prevention beforehand, coordination in the event and punishment afterwards. The mechanism makes the online transaction safe. Theoretic proof and experimental verification indicate the following three problems can be solved effectively: 1) solving the problem, which is difficult to prevent and is that speculative user accumulates the little trusts and squeeze on the large trading; 2) preventing members from cheating by false trading or personation; 3) reducing the arbitration workload of the online business platform.