Author

M. Gani

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Jul 2026

Hybrid Hardening for Robust DNNs Under Adversarial Attacks

Deep Neural Networks are vulnerable to adversarial perturbations, which can cause failures in safety-critical systems. State-of-the-art countermeasures often incur prohibitive overheads, creating a need for cost-efficient robustness strategies. This paper proposes a hybrid hardening technique integrating Triple Modular...

L. D. de Melo, M. Gani, Alberto Bosio et al. · IEEE International Symposium... · 0 citations