摘要
为了更准确地反映出开放式网络环境下实体行为的不确定性和动态性,提出一种基于贝叶斯网络的信任管理方案.该方案显式地加入了上下文信息,并使用一种统计学方法推算出上下文信息对实体行为的影响因子.采用一种上下文间的信任度映射方法,使得实体能够根据一些相关上下文中的信任信息推算出其他实体在陌生上下文中的信任度.仿真结果表明,该方案的信任度估算比其他使用特定算法的系统更精确.
A trust management framework based on Bayesian networks is proposed to reflect the dynamic and uncertain feature of entities＇ behaviors in open network environment more accurately. The context information is considered explicitly and its effect on entity behaviors is inferred statistically. A Bayesian trust mapping approach between the related contexts is also proposed, which allows the application agents to infer the trustworthiness in an unfamiliar context ftom the trust information in other contexts. Simulation results showed that the system can make more accurate trust inferences than ad hoc context-aware systems.
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2008年第3期222-225,共4页
Transactions of Beijing Institute of Technology
基金
国家教委留学回国人员科研启动基金资助项目(1110036820701)
