The trust evaluation model of the existing P2P system is facing the attack behavior of two kinds of strategy malicious nodes： the strategic deception and the dishonest recommendation, which seriously affect the accur...The trust evaluation model of the existing P2P system is facing the attack behavior of two kinds of strategy malicious nodes： the strategic deception and the dishonest recommendation, which seriously affect the accuracy and the effectiveness of the trust evaluation of the model calculation nodes. In view of the disadvantages of the existing models, the author puts forward a trust evaluation model based on the probabilistic method. The model uses the concepts of the subjective trust relationship in the human society, and on the basis of the direct experience and the feedback information, calculate the direct trust and the recommendation trust of the nodes by using the probability statistical method. And through the identification of the importance of the direct experience, distinguish the reliability of the feedback information and recommenders, and improve the effectiveness of the trust evaluation model. The simulation experiment shows that compared with the existing trust evaluation model, this model can effectively restrain the threat of the strategic deception and the dishonesty recommendation, especially the attack of the complex cooperative cheating on the system.展开更多
文摘The trust evaluation model of the existing P2P system is facing the attack behavior of two kinds of strategy malicious nodes： the strategic deception and the dishonest recommendation, which seriously affect the accuracy and the effectiveness of the trust evaluation of the model calculation nodes. In view of the disadvantages of the existing models, the author puts forward a trust evaluation model based on the probabilistic method. The model uses the concepts of the subjective trust relationship in the human society, and on the basis of the direct experience and the feedback information, calculate the direct trust and the recommendation trust of the nodes by using the probability statistical method. And through the identification of the importance of the direct experience, distinguish the reliability of the feedback information and recommenders, and improve the effectiveness of the trust evaluation model. The simulation experiment shows that compared with the existing trust evaluation model, this model can effectively restrain the threat of the strategic deception and the dishonesty recommendation, especially the attack of the complex cooperative cheating on the system.
