The data of nodes in industrial Internet have characteristics of high dimensionality,redundancy and mass and traditional malicious behaviors detection model cannot make a fast and accurate judgment on the malicious behaviors of industrial Internet.A real-time detection method of malicious behaviors in industrial Internet based on feature combination optimization is proposed.The feature combination of industrial Internet malicious behaviors sample data are optimized by improved fast correlation filtering algorithm and principal component analysis algorithm based on singular value decomposi-tion.Based on symmetric uncertainty information measurement index and approximate Markov blanket criterion,feature correlation calculation,redundant feature identification and exclusion are performed.Several candidate feature combina-tions are obtained from different configurations of feature dimensions;Use decision tree evaluator to select the feature com-bination with the highest accuracy;To acquire the optimal feature combination of lower dimension and higher valuable in-formation,the principal component analysis of singular value decomposition is used for further reduce dimension of feature;To classify malicious behaviors samples in industrial Internet through combing extreme gradient boosting algorithm and the optimized feature combination.The proposed method is verified based on Mississippi State University's multi-class power system attack sample data;The experiment demonstrate that training time of the feature combination optimization detection model can be reduced by 57.53%,and the average detection time of a single sample is 0.002 ms,which can be reduced by 23.99%.The accuracy,recall and F1 value of the detection model based on feature combination optimization are improved by 1.11%,1.25%and 1.01%,respectively compared with those before feature optimization.The outstanding advantage of method in this paper is that it can significantly reduce model detection time while improving model detection effect,and can better adapt to the real-time requirements of industrial Internet.
industrial Internet/improved fast correlation filtering algorithm/principal component analysis algorithm based on singular value decomposition/feature combination optimization/extreme gradient boosting/real-time detection of malicious behaviors
维普
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