Abstract

In today's interconnected world, billions of individuals rely on the internet for various activities, from communication and commerce to entertainment and education. However, this widespread connectivity also brings about an increased risk of cyber threats and malicious activities. In response to these challenges, intrusion detection technology has emerged as a vital component of modern cybersecurity strategies. This paper presents a comprehensive literature survey focusing on Internal Intrusion Detection Systems (IIDS) and traditional Intrusion Detection Systems (IDS). These systems utilize a diverse array of data mining and forensic techniques algorithms to monitor and analyze system activities in real-time, thereby detecting and preventing potential security breaches. Additionally, the paper explores the integration of data mining methods for cyber analytics, offering valuable insights into the development and enhancement of intrusion detection capabilities. Through a thorough examination of existing research and methodologies, this study aims to provide a deeper understanding of the evolving landscape of intrusion detection and contribute to the advancement of cybersecurity practices in an increasingly digitized world.

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