摘要
多数P2P网络信任管理模型无法准确计算节点间的推荐信任值,且节点交易过程中不能有效防止恶意推荐。为此,提出一种基于信任迭代的信任管理模型,通过引入信任迭代、推荐可信度和迭代信任值的概念,根据节点间的直接交易经验计算节点间的推荐信任值,将推荐链划分为主链和副链,从而更全面地参考推荐信息,减小因推荐链的取舍对推荐信任值造成的影响,并给出一种新的推荐信任值迭代计算方法,使计算结果更合理。仿真实验结果表明,该模型能够准确地计算推荐信任值,抑制恶意推荐行为。
Most trust management models can not accurately calculate the recommendation trust value in P2P networks,and the nodes can not effectively prevent malicious recommendation in transaction process.Aiming at these problems,a trust management model based on trust iteration is proposed.By introducing the conceptions of trust iteration,recommendation credibility and iteration trust value,it utilizes the direct experience to calculate the recommendation trust value between the nodes,divides the recommendation chains into main chains and subordinate chains to reference the recommendation information comprehensively and reduce the influence of deleting recommendation chains,and presents a new iteration method to calculate recommendation trust value,which makes the results more reasonable.Simulation results show that the model can calculate recommendation trust value accurately and restrain the malicious recommendation.
出处
《计算机工程》
CAS
CSCD
2012年第19期92-95,共4页
Computer Engineering
基金
国家自然科学基金资助项目(60973146)
山东省自然科学基金资助项目(ZR2009GM036)
关键词
信任管理
信任迭代
推荐可信度
迭代信任值
推荐链
trust management
trust iteration
recommendation credibility
iterative trust value
recommendation chain