Real-Time Network Packet Inspection Using Deep Learning Models for Persistent Threat Identification
Nisha Rathore, Yukti Varshney · 2025
This book chapter explores the critical role of real-time network packet inspection in detecting persistent threats within modern cybersecurity infrastructures. With the increasing sophistication of cyberattacks, particularly Advanced Persistent Threats (APTs), traditional defense mechanisms struggle to identify and mitigate evolving network-based threats. Real-time packet analysis, utilizing deep learning models, offers a powerful approach to enhance threat detection capabilities. The chapter delves into the fundamentals of network packet analysis, the nuances of packet transmission and routing, and the application of advanced machine learning algorithms for effective threat identification. Emphasis was placed on correlating packet data, identifying anomalous behaviors, and detecting data exfiltration to safeguard sensitive information. Case studies highlight real-world examples of persistent threats, demonstrating the practical implications of advanced packet inspection techniques. This chapter serves as a comprehensive guide for leveraging network packet analysis and deep learning models to strengthen cybersecurity defenses.