针对实体恶意推荐问题,提出了一种角色分离的信任评估模型(RSTrust).模型将实体在信任评估中承担的角色分为交易角色和推荐角色两类,分别用交易信任度和推荐信任度来描述其可信性,区分不同角色对实体不同信任度的影响；在计算实体全局信任度时,RSTrust将推荐者的全局推荐信任度作为其推荐证据的可信权重,消除恶意推荐对全局信任度计算的干扰.分析和仿真结果表明,模型具有良好的抗恶意推荐能力和收敛性.%To address the recommendation problems from malicious entities, a role separation based trust evaluation model (RSTrust) is proposed in this paper. In RSTrust, roles which entities act during trust evaluation are classified into transaction roles and recommendation roles. Trust on entity is therefore described as transaction trust and recommendation trust according to their associated roles, which leads to the separation of interference between different roles on different trusts. During the calculation of the global trust for an entity, the global recommendation trust of a recommender is used as a trust weight in RSTrust, and the disturbance of recommendation from malicious entities on global trust can be eliminated effectively. Analysis and simulation results demonstrate that RSTrust model has the fine feature of anti-malicious recommendation and good astringency.
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