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
Publication Date
2-1-2023