构造P2P电子商务系统中基于推荐过滤信任模型

Recommendation-based trust model for P2P E-commerce systems

通过对已有工作的分析和对比,选用了一种利用置信因子综合局部声誉和全局声誉的信任评价机制作为研究基础,引入基于集合迭代二分法的过滤方法对推荐节点进行过滤,并提出对评价其他节点评价质量的节点的评价可信度进行了限定来提高模型的准确性和抗攻击能力.同时,为避免恶意节点用诚信买行为来掩盖恶意卖行为的情况,对买家和卖家给对方的评价进行区别对待,考虑了买家和卖家在交易中的不同心理因素.并对本信任评价模型的有效性和抗攻击能力进行了理论分析和仿真实验验证,实验结果说明了与已有的模型相比,该模型能够更快地将信任值收敛到固定值,更准确也更有效地抵抗恶意节点的攻击.

Based on analysis and comparison of the existing work,a reputation-based trust mechanism for P2P E-commerce systems which is based on local reputations and global reputations was chosen,due to its better performance.To improve the accuracy and anti-attack capability of the model,a filtering method based on the iterative dichotomy for aggregate and more comprehensive trust factors are introduced.Besides,to compute the trust value of sellers and buyers,the concept of belief factor was introduced to integrate the local reputation with the global reputation.So the model can avoid peers cover up malicious sales by honest purchases.The effectiveness and resistibility of the proposed trust model were evaluated by theoretical analysis and simulation experiments.The experimental results showed that the proposed trust evaluation model outperforms existing models,it could convergence the trust value to a fixed value sooner and also more accurate and effective to resist malicious attacks.