ENHANCING NETWORK SECURITY IN SDN ENVIRONMENTS: DEVELOPING A DEEP LEARNING-BASED INTRUSION DETECTION SYSTEM FOR EFFECTIVE ANOMALY DETECTION

Shumaila Riffat; Dr. Nasrullah

ENHANCING NETWORK SECURITY IN SDN ENVIRONMENTS: DEVELOPING A DEEP LEARNING-BASED INTRUSION DETECTION SYSTEM FOR EFFECTIVE ANOMALY DETECTION

Authors

Shumaila Riffat
Dr. Nasrullah

Keywords:

Anomaly detection, Model evaluation, SDN security, Deep learning, Intrusion detection systems

Abstract

Use the PDF link to find the full length paper

Downloads

Published

2025-12-10

How to Cite

Shumaila Riffat, & Dr. Nasrullah. (2025). ENHANCING NETWORK SECURITY IN SDN ENVIRONMENTS: DEVELOPING A DEEP LEARNING-BASED INTRUSION DETECTION SYSTEM FOR EFFECTIVE ANOMALY DETECTION. Spectrum of Engineering Sciences, 3(12), 174–190. Retrieved from https://www.thesesjournal.com.medicalsciencereview.com/index.php/1/article/view/1625