Table 10 Comparison of the octet classification experiment results of each model on the CICIDS2017 dataset.

From: A multi-information fusion anomaly detection model based on convolutional neural networks and AutoEncoder

Model

Accuracy

Precision

Recall

F1 Score

CNN1D

0.9786

0.9769

0.9786

0.9764

DT

0.9653

0.9638

0.9653

0.9630

RF

0.9682

0.9667

0.9682

0.9656

SVM

0.9435

0.9439

0.9435

0.9411

KNN

0.9357

0.9245

0.9357

0.9308

AlexNet

0.9790

0.9771

0.9790

0.9770

ResNet

0.9801

0.9783

0.9801

0.9781

MF-CA

0.9851

0.9831

0.9851

0.9831

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