A Detailed Study of Intrusion Detection in Data Mining

Abstract

Network security technology has become crucial in protecting the computing infrastructure of the government and industry. Modern intrusion detection applications are confronted with a variety of issues. These applications must be reliable, extensible, manageable, and minimal in maintenance costs. Data mining-based intrusion detection systems (IDSs) have shown high accuracy, good generalisation to novel types of intrusion, and stable behaviour in a changing environment in recent years. Despite this, there are considerable obstacles in the design and deployment of high-quality IDSs. Data transformations, model deployment, cooperative distributed detection, and sophisticated engineering endeavours are examples of instrumenting components.