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Published Subscription Original Research
Advancements in Intrusion Detection: Tackling Imbalanced Network Traffic with Machine Learning and Deep Learning TechniquesBy Sayed Abdulhayan, Varsha M, Adam Adhil, Hazil Muhammed, Mohamed Favas V.P., Mohammad Fadil
Abstract: Malicious cyberattacks can frequently hide enormous amounts of typical data in unbalanced network traffic. It is very stealthy and obfuscating in cyberspace, which makes it challenging for Network Intrusion Detection Systems (NIDS) to guarantee the precision and promptness of detection. This essay investigates. Machine learning and deep learning are utilized for intrusion detection in imbalanced network traffic. It offers a novel method for addressing the problem of class imbalance termed …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 18–24 Read article →