Performance Analysis of Anomaly-Based Network Intrusion Detection Using Feature Selection and Machine Learning Techniques

Sumedha Seniaray; Rajni Jindal

doi:10.1007/s11277-024-11602-5

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JOURNAL ARTICLE

Performance Analysis of Anomaly-Based Network Intrusion Detection Using Feature Selection and Machine Learning Techniques

Sumedha Seniaray Rajni Jindal

Year: 2024 Journal: Wireless Personal Communications Vol: 138 (4)Pages: 2321-2351 Publisher: Springer Science+Business Media

DOI: 10.1007/s11277-024-11602-5

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Keywords:

Computer science Feature selection Intrusion detection system Anomaly detection Artificial intelligence Selection (genetic algorithm) Machine learning Network security Feature (linguistics) Intrusion Data mining Pattern recognition (psychology) Computer 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

Spam and Phishing Detection

Physical Sciences → Computer Science → Information Systems

Performance Analysis of Anomaly-Based Network Intrusion Detection Using Feature Selection and Machine Learning Techniques

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