Building an intrusion detection system on UNSW-NB15: Reducing the margin of error to deal with data overlap and imbalance

Article (Web of Science), Early Access (Web of Science)

• cited authors: Zoghi, Zeinab; Serpen, Gursel
• publication date: August 22, 2024
• webpage: Web of Science
• published in: CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE Journal
• category: COMPUTER SCIENCE, THEORY & METHODS Category

keywords

• UNSW-NB15 dataset
• anomaly detection
• binary classification
• class imbalance
• class overlap
• cybersecurity analytics
• ensemble learning
• intrusion detection systems (IDS)
• machine learning
• multi-class classification
• network security