Adversarially Optimized Multi-Space Prototypical Network for Intrusion Detection in 5G-Enabled IoT Systems

Existing state-of-the-art IDS solutions in 5G-enabled IoT, including deep convolutional architectures, are constrained by data scarcity, limited edge resources, and poor robustness in few-shot learning (FSL) scenarios with scarce attack samples. To address these limitations, we propose MSPL-IDS, a r...

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Bibliografski detalji

Glavni autori:	Shahid Latif, Jawad Ahmad, Wadii Boulila, Djamel Djenouri
Format:	Artigo
Jezik:	Inglês
Izdano:	IEEE 2026-01-01
Serija:	IEEE Transactions on Machine Learning in Communications and Networking
Teme:	Adversarial machine learning cybersecurity few-shot learning intrusion detection prototypical network
Online pristup:	https://ieeexplore.ieee.org/document/11433812/
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