AINeutralarXiv – CS AI · 7h ago6/10
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CEAR: Certified Ensemble Adversarial Robustness in DNNs
Researchers propose CEAR, an ensemble-based defense mechanism combining empirical and certified robustness techniques to protect deep neural networks against adversarial attacks. The method uses varying Gaussian noise, temperature adjustments, and novel voting mechanisms while extending randomized smoothing to ensemble classifiers, demonstrating improved certified accuracy across benchmark datasets.