基于电力调控数据挖掘的混合IDS研究

为适应大数据背景,提出一种基于电力调控数据挖掘的混合IDS自动构建方法。该系统利用公共路径挖掘算法,将同步相量测量数据和调控日志相融合,自动学习各类场景,并将系统状态遍历匹配到公共路径做出分类决策。为验证该方法,搭建了一个包含25个场景的试验平台,并对三母线两馈线系统进行训练和评估,其中90.2%的场景被正确分类。结果表明该IDS具有较高检测精度,可适用于电力调控要求的任务环境。

Research on Hybrid IDS Based on Data Mining forElectric Power Regulation System

In order to adapt to the big data background a hybrid intrusion detection system(IDS)automatic construction method based on data mining of power regulation is proposed.The IDS integrates synchronous phasor measurement data and electric power regulation log data based on common path mining algorithm,automatically learns various scenarios,and matches system state traversal to common path to make classification decisions.To verify the method,a test platform containing 25 scenarios was built,and the three-bus two-feeder system was trained and evaluated.90.2%of the scenarios were correctly classified.The results show that the IDS has high detection accuracy and can be applied to the task environment required by power regulation and control.