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