LARAR enhances adversarial robustness in network intrusion detection by using layer-wise adaptive regularization and auxiliary classifiers, achieving 95.01% clean accuracy and improved defense against FGSM, PGD, and transfer attacks on UNSW-NB15.
Scientific Reports 15(1), 14177 (2025) 23
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Enhancing Adversarial Robustness in Network Intrusion Detection: A Layer-wise Adaptive Regularization Approach
LARAR enhances adversarial robustness in network intrusion detection by using layer-wise adaptive regularization and auxiliary classifiers, achieving 95.01% clean accuracy and improved defense against FGSM, PGD, and transfer attacks on UNSW-NB15.