作　　者： (游静）; (上官经伦）; (徐守坤）; (李千目）; (王印海）;

机构地区： 常州大学信息科学与工程学院,江苏常州213164

出　　处： 《软件学报》 2017年第9期2354-2369,共16页

摘　　要： 分布式动态信任模型作为适用于云计算环境下的访问管理机制已经得到广泛研究,然而现有的许多信任模型忽视了对信任数据可靠性的评估,导致推荐信任不可靠时出现模型失效.针对这一问题,提出了一种考虑信任可靠度的分布式动态信任管理模型DDTM-TR.首先使用可靠度对信任进行评估,降低不可靠数据对直接信任、推荐信任、综合信任计算的影响;然后,选择多个待选节点计算它们的综合信任,并以计算出的综合信任为概率,随机选择待选节点进行交互;在交互结束后,根据交互满意度反馈修正节点的可靠度.仿真实验结果表明:DDTM-TR模型在处理恶意服务、恶意推荐方面都优于对比模型,并且能够通过反馈算法进一步降低判断的失败率. Distributed dynamic trust model, as a new access management mechanism which applies to cloud computing environment, has been studied extensively. However, many existing trust models ignore the reliability of trust data and lead to failure when facing malicious recommendation. To solve this problem, this article proposes a new model named DDTM-TR （distributed dynamic trust management model based on trust reliability）. Firstly, in order to reduce the bad effects of unreliable data on direct trust, recommendation trust and integrated trust, the reliability of trust data is evaluated. Second, several candidate nodes are selected and their integrated trust values are calculated, and one of them is selected randomly according to the stochastic decision algorithm based on their integrated trust values. Finally, the node reliability is updated according to the feedback after the interaction. The experiments demonstrate that DDTM-TR model performs better than the compared models in resisting malicious service and malicious recommendation, and the failure rate can be reduced further by the feedback algorithm.

关 键 词： 动态信任模型 可靠度 信任管理 推荐信任