EVOLUTION OF INTRUSION DETECTION: THEORETICAL FOUNDATIONS, SYSTEM ARCHITECTURES, AND REAL- WORLD PRACTICES

Abstract

With the exponential growth of digital networks and the increasing sophistication of cyber threats, intrusion detection systems (IDS) have emerged as a critical component in maintaining information security. IDS technologies monitor, detect, and respond to unauthorized activities or anomalies within networked environments. This article explores the foundational theories underpinning intrusion detection, examines prevalent frameworks and architectures, and

analyzes established and emerging models such as signature-based, anomaly-based, and hybrid detection systems. Additionally, it highlights practical implementations of IDS across various industries and reviews the effectiveness of current approaches using performance metrics like accuracy, false positive rates, and detection latency. The paper concludes with a discussion on the challenges facing modern IDS, including scalability, evasion techniques, and the integration of artificial intelligence, and outlines future research directions to enhance adaptive and

intelligent intrusion detection mechanisms.