基于大数据技术的智能电网异常入侵动态检测方法

Dynamic detection method of abnormal intrusion in smart grid based on big data technology

为避免异常入侵信息过度占据电网存储环境,方便智能电网主机对入侵参量的动态检测与处理,提出基于大数据技术的智能电网异常入侵动态检测方法。在大数据处理架构中,确定异常行为指征的取值范围,联合已获取数据样本,求解入侵风险系数的计算结果,完成基于大数据技术的入侵信息处理。根据动态检测目标定义式,计算威胁性度量指标的具体数值,通过构建损失函数的方法,实现智能电网异常入侵信息的动态检测。对比实验结果表明,应用所提方法后,入侵信息在电网环境中的存储总量低于35%,符合动态处理电网异常入侵信息的应用需求。

In order to avoid the abnormal intrusion information occupying the power grid storage environment excessively and facilitate the smart grid host to dynamically detect and process the intrusion parameters,a dynamic detection method of abnormal intrusion in smart grid based on big data technology is proposed.In the big data processing architecture,determine the value range of abnormal behavior indicators,combine the obtained data samples,solve the calculation results of intrusion risk coefficient,and complete the intrusion information processing based on big data technology.According to the definition of dynamic detection target,the specific value of threat measurement index is calculated,and the dynamic detection of abnormal intrusion information in smart grid is realized by constructing loss function.The comparative experimental results show that the total amount of intrusion information stored in the power grid environment after the application of the proposed method is less than 35%,which meets the application requirements of dynamically processing abnormal intrusion information in the power grid.