NETWORK TRAFFIC ANALYSIS FOR DETECTING CYBER ATTACKS ( October 2026)

Most attacks have to traverse a network at some point, and when they do so, they leave traces in the traffic.This paper investigates how those traces can be collected, measured and turned into alerts.We cover the most common ways to collect traffic data (packet captures, flow records and logs), the types of characteristics that are generally useful, and three main families of detection methods: signature-based, statistical and machine learning-based.We also describe how several well-known attacks (port scans, denial of service, brute force and botnet command-and-control) manifest themselves on the wire A step-by-step analysis pipeline is presented, as well as the most common public datasets used for evaluation and the corresponding metrics.Finally, we discuss the major challenges that remain in this area: encrypted traffic, class imbalance, concept drift and the gap between laboratory test results and real-world network deployments.The goal is to provide a clear, practical overview for students and junior security analysts rather than presenting a novel algorithm.