由于网络外界病毒入侵的隐蔽性极高、入侵类型较多,病毒难以被全面地被感知,导致电网调度自动化系统运行安全受到威胁。为提升电网调度自动化系统网络的安全性,提出基于随机矩阵理论(Random Matrix Theory , RMT)的电网调度自动化系统网络安全态势感知技术。采集电网调度自动化系统网络安全信息数据,构建病毒入侵环境下的安全状态分布模型,并利用该模型完成电网调度系统网络安全态势特征信息的提取。采用RMT中的M-P模型及单环定律对网络安全态势特征值在随机矩阵内的分布情况进行谱分析,根据特征值分布状态获取网络安全态势在稳定情况及异常情况下的变换规律,实现电网调度系统网络安全态势感知。实验结果表明,通过对该方法开展安全态势感知测试,验证了该方法应用在电网调度系统中组件安全态势感知及网络安全态势感知的精准度均较高,体现了该方法的有效性。
英文摘要:
Due to the high concealment of virus intrusion outside the network and many types of intrusion, it is difficult for the virus to be fully sensed, which leads to a threat to the operation security of the power grid dispatching automation system. In order to improve the network security of power grid dispatching automation system, a network security situational awareness technology of power grid dispatching automation system based on RMT is proposed. Collect the network security information data of the grid dispatching automation system, construct the security state distribution model under the virus invasion environment, and use the model to complete the extraction of the network security situation characteristic information of the grid dispatching system. The M-P law and the single-loop law in RMT are used to analyze the distribution of the eigenvalues of the network security situation in the random matrix. System network security situational awareness. The experimental results show that by carrying out the security situational awareness test of the method, it is verified that the method is applied to the power grid dispatching system with high accuracy of component security situational awareness and network security situational awareness, which reflects the effectiveness of the method.