基于信任域的分布式动态信任管理模型

针对现有动态信任模型在适应性、健壮性和激励机制方面存在的不足，提出一种分布式信任评估模型。引入时间调整函数和稳定度函数，分别解决了模型的动态适应问题和总体信任计算过程中的权重分配问题。综合考虑交互历史和信任分布情况制定相应评估策略，节约了计算资源。此外，通过给出一种直接推荐考察表，有效地识别和限制了故意夸大、恶意诋毁等虚假推荐行为，保证了模型的健壮性。仿真实验表明，该模型在抵御更加复杂的恶意攻击和恶意欺骗等行为方面，体现了良好的准确性、收敛性和适应性。

Distributed dynamic trust management model based on trusted domains

In order to improve the flexibility of trust computing in the model, the trusted domain was divided into three decision domains. Problem of adaptability was solved by introducing time adjustment into the model. Stability function tackled weight distribution problem during calculating total value. Consideration of interaction history and the distribution of trust while making evaluation strategy saved computing resources. Moreover, investigation table about direct recommendation entity was put forward to identify and restrict false recommendation problems effectively. A better result of accuracy, convergence and adaptability in dealing with complex malicious attacks and fraud in the model was indicated after simulation results.