A whitelist and blacklist-based co-evolutionary strategy for defensing against multifarious trust attacks

With electronic commerce becoming increasingly popular, the problems of trust have become one of the main challenges in the development of electronic commerce. Although various mechanisms have been adopted to guarantee trust between customers and sellers (or platforms), trust and reputation systems are still frequently attacked by deceptive, collusive, or strategic agents. Therefore, it is difficult to keep these systems robust. It has been mentioned that a combined usage of both trust and distrust propagation can lead to better results. However, little work has been known to realize this insight successfully. Besides, literatures either use a social network with trust/distrust information or use one advisor list in evaluating all sellers, which leads to the lack of pertinence and inaccuracy of evaluation. This paper proposes a defensing strategy called WBCEA, in which, each buyer agent is modeled with two attributes (i.e., the trustworthy facet and the untrustworthy facet) and two lists (i.e., the whitelist and the blacklist). Based on the social network that are constructed and maintained according to its whitelist and blacklist, the honest buyer agent can find trustable buyers and evaluate the candidate sellers according to its own experience and ratings of trustable buyers. Experiments are designed and implemented to verify the accuracy and robustness of this strategy. Results show that our strategy outperforms existing ones, especially when majority of buyers are dishonest in the electronic market.