摘要
针对基于可信计算的网格行为信任模型,运用波动信息能量变换给出了根据实体的交互经验和交互时间计算历史信任值和直接信任值的方法;用Hausdorff距离构造了函数相关程度的算法,进而给出了自我信任值的计算方法。通过采用门限值作为平均值、自我信任值为偏差量的正态分布函数构造了推荐信任值的更新函数,给出了域间评估流程图,并用一个有2 000个实体的区域网格进行域内数据更新实验。分析结果说明了各评估算法的合理性和有效性。
For the quantitative assignment of the grid behaviors trust model based on trusted computing,it gives an algorithm of calculating the direct trust values and the history trust values from interactive experience and interactive time using fluctuation energy conversion,makes a function correlation algorithm using hausdorff function,and in turn gives a method of calculating the self-confidence value,makes an update function using a normal distribution function with the threshold as average value and self-confidence value as deviation,gives the inter-domain evaluation process,finally shows the reasonableness and effectiveness of the assessment method by running the update process and analysising the result of the data of a regional grid with 2 000 entities.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2010年第5期587-590,共4页
Geomatics and Information Science of Wuhan University
基金
国家985工程信息平台建设资助项目(0X0007)
福建省自然科学基金资助项目(2009J01304)
关键词
网格
行为信任
可信计算
量化评估
直接信任值
更新函数
grid
behavior trust
trusted computing
quantitative assessment
direct trust value
update function
