Intrusion Detection System

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Bol 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.

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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.

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Pages: 92, Paperback, LAP Lambert Academic Publishing


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Merk LAP LAMBERT Academic Publishing
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  • 9786207646845
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