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1篇 您的检索式：作者名="Menglong Ba"

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		题名	作者	年代	出处	被引量
	1	RP-NBSR: A Novel Network Attack Detection Model Based on Machine Learning显示文摘The rapid progress of the Internet has exposed networks to an increasednumber of threats. Intrusion detection technology can effectively protect networksecurity against malicious attacks. In this paper, we propose a ReliefF-P-NaiveBayes and softmax regression (RP-NBSR) model based on machine learningfor network attack detection to improve the false detection rate and F1 score ofunknown intrusion behavior. In the proposed model, the Pearson correlation coef-ficient is introduced to compensate for deficiencies in correlation analysis betweenfeatures by the ReliefF feature selection algorithm, and a ReliefF-Pearson correlation coefficient (ReliefF-P) algorithm is proposed. Then, the Relief-P algorithm isused to preprocess the UNSW-NB15 dataset to remove irrelevant features andobtain a new feature subset. Finally, naïve Bayes and softmax regression (NBSR)classifier is constructed by cascading the naïve Bayes classifier and softmaxregression classifier, and an attack detection model based on RP-NBSR is established. The experimental results on the UNSW-NB15 dataset show that the attackdetection model based on RP-NBSR has a lower false detection rate and higherF1 score than other detection models.	Zihao Shen Hui Wang Kun Liu Peiqian Liu Menglong Ba MengYao Zhao	2021	Computer Systems Science & Engineering2021，37，4：	0

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