An efficient blockchain-based ANN framework for SDN-IoT cyberdefense

The development of new technologies and improved modeling skills brought forth by the Internet of Things (IoT) has helped to raise living standards in the contemporary world. The IoT platform’s widespread use of portable, unsecured devices has resulted in a sharp increase in cyberattacks. This study suggests a safe Internet of Things network that integrates blockchain technology, Software Defined Networking (SDN), and Artificial Neural Networks (ANNs) for a well-defense strategy to address these security concerns. The distributed SDN architecture, having more than one controller, ensures scalability and redundancy, which fixes the limitations of traditional centralized control. SDN controller communications are maintained in an immutable record using blockchain technology, removing single points of failure through cryptographically secure, distributed record keeping. Using ANNs, the system can perform real-time analysis and pattern recognition of traffic for Distributed Denial of Services attack detection and prevention. The framework is validated experimentally using a novel SDN intrusion detection dataset, achieving 98.4% accuracy, 88.7% recall, and an F1-score of 93.4%. These promising results demonstrate the potential of the framework for deploying in practice, operating over IoT networks to mitigate the novelty of emerging cybersecurity risks. By enabling the programmability of SDN, trustless security of blockchain, and adaptive learning of ANNs, the proposed architecture provides a significant improvement in IoT security.