Creating an Intrusion Detection System Using Machine Learning
Introduction to Intrusion Detection Systems (IDS) Intrusion Detection Systems (IDS) are crucial components of modern cybersecurity infrastructure, designed to detect and alert on potential security threats in real-time. Traditional IDS systems rely on signature-based detection, which can be ineffective against unknown or zero-day attacks. Machine learning (ML) offers a promising solution by enabling systems to learn from data and detect anomalies that may indicate malicious activity. Steps to Create an IDS Using Machine Learning 1. Data Collection The first step in creating an ML-based IDS is to collect relevant data. This typically involves gathering network traffic data, which can be done using tools like Wireshark or by collecting logs from network devices. The dataset should include both normal and malicious traffic to train the model effectively. ...