讨论了信任关系的随机性和模糊性共存以及相互融合问题。分析云模型描述不确定性概念的方法和实现定性语意与定量数值相互转换的算法，提出了基于云理论的信任评估模型—信任云。该模型提出云特征参数表达的信任传递和合并算法，在精确描述信任期望值的同时，通过熵和超熵刻画了信任的不确定性。相对于传统的信任评估策略，该模型获取的信任值包含更多的语意信息，更适合作为信任决策的依据。

At present, the existing descriptions of trust by trust valuation models lack comprehensiveness. To solve this problem, this paper discusses the co-existence and integration of fuzziness and randomness of trust relation, analyzes the ways cloud models describe uncertain concepts and the algorithms cloud models transform between qualitative concepts and their quantitative expressions, and presents trust cloud, a trust evaluation model based on cloud theory. This model provides the algorithms of trust information transfer and combination described by digital characteristics. While describing accurate trust expectation, this model portrays the uncertainty through entropy and hyper entropy. Compared with traditional trust valuation models, trust values obtained in this model contains more semantic information, indicating that valuation results from the model are more suitable as evidence for decision-making on trust.

路峰（1976－），男，江苏沐阳县人，南京理工大学博士研究生，主要研究方向为网格计算和网络安全