Lightweight IoT Intrusion Detection via Feature and Sample Reduction With Multi-Client Ensemble for Zero-Day Attacks

The rapid proliferation of the Internet of Things (IoT) exposes heterogeneous and resource-constrained devices to an increasingly diverse and evolving range of network attacks. Conventional centralized intrusion detection systems (IDS) and complex machine learning models often experience high comput...

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Autors principals:	Hongwei Zhang, Darshana Upadhyay, Marzia Zaman, Srinivas Sampalli
Format:	Artigo
Idioma:	Inglês
Publicat:	IEEE 2026-01-01
Col·lecció:	IEEE Access
Matèries:	Data compression dimensionality reduction ensemble learning feature selection Internet of Things intrusion detection system
Accés en línia:	https://ieeexplore.ieee.org/document/11398098/
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