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March 3, 2026
DiMCA: A novel P4-powered framework using machine learning for adaptive defense against combined DDoS and ARP spoofing attacks in SD-IoT networks
MG
Manal Gafar
Egyptian Universities Network
SE
Saied M. Abd El-atty
MA
Mohamed S Arafa
Key Points
Adaptive defense significantly improves resilience against combined DDoS and ARP spoofing attacks in SD-IoT networks.
Framework employs machine learning algorithms to detect and respond to threats in real-time, enhancing security.
Developed for Software Defined Internet of Things (SD-IoT) environments to mitigate evolving cyber threats.
Findings may inform further advancements in cybersecurity strategies for integrated network systems.
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Cite This Study
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Gafar et al. (Wed,) studied this question.
synapsesocial.com/papers/69a75bfbc6e9836116a24462
https://doi.org/https://doi.org/10.1016/j.compeleceng.2025.110929
DiMCA: A novel P4-powered framework using machine learning for adaptive defense against combined DDoS and ARP spoofing attacks in SD-IoT networks | Synapse