Abstract: We propose an adversarial attack for machine-learning-based network intrusion detection systems that selectively alters only the most influential features. Unlike conventional attacks such ...
Abstract: 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 ...
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