【摘要】 为解决高效实时开源工业以太网协议Ethernet Powerlink面临的日益严峻的安全问题,提出一种基于Powerlink通讯协议的异常检测方法。针对Powerlink工控通讯网络的通信特点,通过对Powerlink工业控制通信网络的特殊性和安全性分析,以及可能遭受的恶意入侵行为的探索,提取可以表征通信行为的有效数据特征,建立SVDD异常检测分类模型,并通过改进的PSO算法对SVDD参数进行寻优,使检测精度进一步提高,优化异常检测模型。仿真结果表明,该方法能有效检测出异常的恶意攻击行为,提高工控通信网络的安全运行。更多还原

【Abstract】 To deal with the increasingly serious security problem faced by the efficient and real-time Ethernet industrial protocol Ethernet Powerlink,an anomaly detection method based on Powerlink communication protocol was proposed.According to the particularity of Powerlink industrial control network,the security of Powerlink communication system was analyzed from the perspective of industrial safety,and the data flow characteristics were extracted from the communication network by revealing the abnormal attack behavior,a support vector data description(SVDD)anomaly detection algorithm model was built to identify abnormal network traffic.The improved particle swarm optimization(PSO)was used to optimize the model parameters,which further improved the detection accuracy.Experimental simulation and comparison with other algorithms show that the proposed method can detect abnormal malicious attacks effectively,and improve the safe operation of industrial communication network.更多还原