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Corresponding Author

Sardar KH. Hassan

Authors ORCID

0000-0002-6620-8627

Document Type

Research Article

Abstract

Computer systems and network infrastructures are still exposed to many security risks and cyber-attack vulnerabilities despite advancements of information security. Traditional signature-based intrusion detection systems and security solutions by matching rule-based mechanism and prior knowledge are insufficient of fully protecting computer networks against novel attacks. For this purpose, Anomaly-based Network Intrusion Detection System (A-NIDS) as cyber security tool is considered for identifying and detecting anomalous behavior in the flow-based network traffic alongside with firewalls and other security measures.The main objective of the research is to improve the detection rate and reduce false-positive rates of the classifier using anomaly-based technique.

Keywords

Intrusion Detection System, Anomaly detection, Intelligent Technique, Cyber-Attack, Deep Learning, Machine Learning

Publication Date

2-1-2023

Included in

Life Sciences Commons

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