Autoperman: Automatic Network Traffic Anomaly Detection with Ensemble Learning

Shangbin Han; Qianhong Wu; Han Zhang; Bo Qin; Jiangyuan Yao; Willy Susilo

doi:10.1007/978-3-031-06761-7_49

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Autoperman: Automatic Network Traffic Anomaly Detection with Ensemble Learning

Shangbin Han Qianhong Wu Han Zhang Bo Qin Jiangyuan Yao Willy Susilo

Year: 2022 Communications in computer and information science Pages: 616-628 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-031-06761-7_49

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Keywords:

Hyperparameter Computer science Support vector machine Anomaly detection Machine learning Artificial intelligence Data mining Classifier (UML) Training set Random forest Supervised learning Anomaly (physics) Data set Labeled data Set (abstract data type) Artificial neural network

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Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

Internet Traffic Analysis and Secure E-voting

Physical Sciences → Computer Science → Artificial Intelligence

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Autoperman: Automatic Network Traffic Anomaly Detection with Ensemble Learning

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