邬蓉蓉,黎新,宾冬梅.基于XGBoost算法的智能电网信息攻击识别模型[J].电测与仪表,2023,60(1):64-70. Wu Rongrong,Li Xin,Bin Dongmei.A network attack identification model of smart grid based on XGBoost[J].Electrical Measurement & Instrumentation,2023,60(1):64-70.
基于XGBoost算法的智能电网信息攻击识别模型
A network attack identification model of smart grid based on XGBoost
After the smart grid suffers from network attacks, the measured data containing the mixture of the multi-dimensional fault state data, attack state data and normal data. It is difficult to identify specific attack types from the measurement data. Aiming at the above problems, this paper proposes a smart grid network-attack identification model based on Extreme Gradient Boosting (XGBoost) algorithm. Then, based on the feature selection method of maximum correlation and minimum redundancy (MRMR), the optimal feature subset of information attack events is extracted to reduce the data dimension and improve the model"s recognition efficiency of information attack. Finally, a XGBoost classifier is trained on the optimal feature subset to obtain the information attack identification model, and the performance of the model is evaluated by accuracy and recall. The experimental results proved that the network attack identify model improves the detection accuracy of smart grid information attacks significantly.
