Borderline SMOTE Algorithm and Feature Selection-Based Network Anomalies Detection Strategy

Borderline SMOTE Algorithm and Feature Selection-Based Network Anomalies Detection Strategy

This paper proposes a novel network anomaly detection framework based on data balance and feature selection. Different from the previous binary classification of network intrusion, the network anomaly detection strategy proposed in this paper solves the problem of multiple classification of network...

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Bibliographic Details
Main Authors: Yong Sun, Huakun Que, Qianqian Cai, Jingming Zhao, Jingru Li, Zhengmin Kong, Shuai Wang
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Energies
Subjects:
network intrusion detection
machine learning
borderline SMOTE
information gain ratio
Online Access:https://www.mdpi.com/1996-1073/15/13/4751

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