Anomaly-based Network Intrusion Detection System using Deep Intelligent Technique

Authors

Sardar KH. Hassan, Department of Computer Science, Soran UniversityFollow
Muhammadamin A. Daneshwar, Department of Computer Science, Soran University

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

How to Cite This Article

Hassan, Sardar KH. and Daneshwar, Muhammadamin A. (2023) "Anomaly-based Network Intrusion Detection System using Deep Intelligent Technique," Polytechnic Journal: Vol. 12: Iss. 2, Article 11.
DOI: https://doi.org/10.25156/ptj.v12n2y2022.pp100-113

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Publication Date

2-1-2023