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.