KAN-MID: A Kolmogorov-Arnold Networks-Based Framework for Malicious URL and Intrusion Detection in IoT Systems

The growing sophistication of cyberattacks, especially with the ubiquity of the Internet of Things (IoT), highlights the urgent need for stronger detection and protection strategies. With millions of victims impacted by escalating threats and facing substantial financial repercussions, the importanc...

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Hlavní autoři:	Frederic Rizk, Rodrigue Rizk, Dominick Rizk, Patrick Rizk, Chee-Hung Henry Chu
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IEEE 2025-01-01
Edice:	IEEE Access
Témata:	Cyber attacks deep learning Internet of Things (IoT) intrusion detection systems (IDS) Kolmogorov-Arnold networks (KANs) malicious URL detection
On-line přístup:	https://ieeexplore.ieee.org/document/11146737/
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