WANG Hai-Cheng, GUI Xiao-Lin, WANG Hai-Chen
To ensure the security of the transaction in P2P network, a new network security model based on classification management of trading nodes is proposed. Through classification statistics of failure events in the trade between the local node and other nodes, the trade failure events are divided into malicious attacks, bad quality and so on, so that malicious nodes can be detected and controlled timely and correctly. According to transaction history records, Support Vector Machine(SVM) classifier is used to divide trading nodes into trust nodes, strange nodes and malicious nodes. The trust node list and the malicious node list are established to exclude the malicious nodes from trading. According to the statistical data of feedbacks from the other nodes, Bayesian classifier is used for the classification of the evaluated nodes. The model dynamically counts the feedback behavior condition, divided the feedback behavior into the honest feedback, the malicious feedback and so on. Experimental results show that compared with the existing trust model, the model proposed can obtain higher examination rate over malicious acts and the higher transaction success rate.