Intrusion Detection System

Software-Defined Networks (SDN) offer enhanced network management and control, but also introduce new security vulnerabilities. This book presents a comprehensive approach for intrusion detection in SDN environments, combining Elliptic Curve Cryptography (ECC) for secure data transmission with a hybrid machine learning model for accurate attack classification. The system utilizes the Curve25519-Dalek-Hash (CDH) key exchange protocol to encrypt sensitive network data, ensuring confidentiality and integrity. A hybrid model integrating XG Boost and Light GBM algorithms is employed for efficient and accurate attack detection. The proposed system is evaluated on a real-world SDN dataset, demonstrating high accuracy and efficiency in identifying malicious activities.

• | Author: Kanimozhi D
• | Publisher: LAP Lambert Academic Publishing
• | Publication Date: Sep 26, 2024
• | Number of Pages: 92 pages
• | Binding: Paperback or Softback
• | ISBN-10: 6207646843
• | ISBN-13: 9786207646845