Intrusion Detection System Project
Project Overview This project implements an Intrusion Detection System (IDS) to detect potential network intrusions using anomaly detection. The system processes network traffic data (e.g., from Wireshark captures) and employs the Isolation Forest algorithm from Scikit-learn to identify anomalous behavior that may indicate intrusions, such as unauthorized access or malicious activities. Objectives Analyze network traffic data to extract relevant features (e.g., packet size, protocol type, source/destination IPs). Apply the Isolation Forest algorithm to detect anomalies in network traffic. Provide a scalable and modular system for real-time or batch intrusion detection. Include comprehensive documentation and instructions for setup and usage. Skills and Tools Skills : Cybersecurity, Machine Learning, Networking Tools : Python, Wireshark, Scikit-learn, Pandas, NumPy System Design The IDS consists of the following components: Data Collection : Network traffic data is captured using...