DDoS Mitigation in IoT Using Machine Learning and Blockchain Integration

The Internet of Things (IoT) has brought about flexible data management and monitoring, but it is increasingly vulnerable to distributed denial-of-service (DDoS) attacks. To counter these threats and bolster IoT device trust and computational capacity, we propose an innovative solution by integratin...

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Veröffentlicht in:IEEE networking letters 2024-06, Vol.6 (2), p.152-155
Hauptverfasser: Ibrahim El Sayed, Ammar, Abdelaziz, Mahmoud, Hussein, Mohamed, Elbayoumy, Ashraf D.
Format: Artikel
Sprache:eng
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Zusammenfassung:The Internet of Things (IoT) has brought about flexible data management and monitoring, but it is increasingly vulnerable to distributed denial-of-service (DDoS) attacks. To counter these threats and bolster IoT device trust and computational capacity, we propose an innovative solution by integrating machine learning (ML) techniques with blockchain as a supporting framework. Analyzing IoT traffic datasets, we reveal the presence of DDoS attacks, highlighting the need for robust defenses. After evaluating multiple ML models, we choose the most effective one and integrate it with blockchain for enhanced detection and mitigation of DDoS threats, reinforcing IoT network security. This approach enhances device resilience, presenting a promising contribution to the secure IoT landscape.
ISSN:2576-3156
2576-3156
DOI:10.1109/LNET.2024.3377355