nids-ibm-autoai

Network Intrusion Detection System using IBM Watson AutoAI and NSL-KDD dataset

Network Intrusion Detection System (NIDS) using IBM Watson AutoAI

This project implements a machine learning-based Network Intrusion Detection System (NIDS) using IBM Watson AutoAI and the NSL-KDD dataset. The system is capable of classifying network traffic as normal or various types of cyber-attacks (e.g., DoS, Probe, R2L, U2R). It includes an automated ML pipeline, a deployed model as a REST API, and a frontend for real-time predictions.

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🔍 Project Overview

• Dataset: NSL-KDD (network traffic logs labeled with attack categories)
• AutoML Tool: IBM Watsonx AutoAI
• Model Chosen: Decision Tree Classifier (Pipeline 9, Accuracy: 98%)
• Deployment: IBM Watson Machine Learning (WML) — Online Deployment

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