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Found 3 papers, 2 papers with code
MIMIR: Masked Image Modeling for Mutual Information-based Adversarial Robustness
However, these methods still follow the design of traditional supervised adversarial training, limiting the potential of adversarial training on ViTs.
IB-RAR: Information Bottleneck as Regularizer for Adversarial Robustness
In this paper, we propose a novel method, IB-RAR, which uses Information Bottleneck (IB) to strengthen adversarial robustness for both adversarial training and non-adversarial-trained methods.
Universal Soldier: Using Universal Adversarial Perturbations for Detecting Backdoor Attacks
This paper proposes a backdoor detection method by utilizing a special type of adversarial attack, universal adversarial perturbation (UAP), and its similarities with a backdoor trigger.
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