一种基于信任值的雾计算动态访问控制方法

A Dynamic Access Control Method for Fog Computing Based on Trust Value

雾计算服务对象是数量庞大、形态各异的物联网设备,且多应用于工业控制、车联网、智慧医疗等形态各异的实时场景,对其访问控制系统动态性、适应性和时延都提出了比较苛刻的要求。传统的访问控制方法不能满足雾计算系统要求,针对这一问题,文章提出了一种基于信任值的动态访问控制方法,从日志数据中提取设备行为特征,使用训练好的机器学习模型计算当前活跃设备的信任值,使用灰度化方法计算当前不活跃设备的信任值,并作为访问决策的依据。该方法从复杂的设备行为特征中提取信任值作为单一访问决策依据,既可以实现快速动态的访问控制,又能迅速迁移到不同应用场景,具备良好的适应性。通过实验对该访问控制方法进行了验证,实验结果表明该方法在运行速度、适应性等方面表现良好。

Fog computing is usually applied to industrial control,Internet of vehicles,intelligent medical and other real-time scenarios.These scenarios require dynamic,adaptive and low delay access control methods.Traditional access control methods are not suitable.This paper proposes a dynamic access control method based on trust value.This method extracts device behavior features from log files.And then calculates the trust value of active devices using machine learning models,while the trust value of inactive devices is calculated using grayscale method.The method proposed in this paper can not only realize fast and dynamic access control,but also can be easily migrated to multiple scenarios.The author have implemented the method based on equipment and data set provided by the research group.