Network Traffic Analysis and Intelligent Mitigation Using Multi-Class Machine Learning
Network Traffic Analysis and Intelligent Mitigation Using Multi-Class Machine Learning
Authors:
K. Ranjith Reddy, B. Bharath Abhinav, M. Goutham
Abstract:
Modern networks face increasing cyber threats such as DDoS, PortScan, BruteForce, and Web attacks. Traditional IDS lack mitigation validation. This paper proposes a multi- class machine learning framework using Random Forest on CICIDS2017 dataset. The system integrates detection, mitigation simulation, and visualization. Experimental results show 99.98% accuracy and improved network performance.
Index Terms:
Intrusion Detection, Machine Learning, Ran- dom Forest, Cybersecurity
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