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Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

ICML 2023 · Adversarial robustness and security › Certified and empirical robustness · approach: Provable robust learning guarantees

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
replace coordinate-descent (K-hot SLIDE-style) attack with Euclidean-geometry gradient step (Fast-EG-l1)one-step l1 adversarial training · CIFAR10, CIFAR100, ImageNet100AA robust accuracy (%): 50.27 vs 48.35 (NuAT best baseline) on CIFAR10; 38.03 vs 36.46 on CIFAR100; 46.74 vs 45.82 on ImageNet100Helped
use multi-epsilon training budget (ϵtrain=2ϵ) instead of ϵtrain=ϵ (ablation)Fast-EG-l1 · CIFAR10 (ϵ=12)AA robust accuracy (%): 50.27 vs 38.15Helped
multi-epsilon training budget larger than ϵ (1.5ϵ to 3ϵ) (ablation)Fast-EG-l1 · CIFAR10 (ϵ=12)clean accuracy (%): clean 78.35 at 1.5ϵ vs 70.05 at 3ϵ; large ϵtrain lowers clean accuracyHurt
add nuclear norm regularization to Fast-EG-l1 with small weight (ablation)Fast-EG-l1 · CIFAR10, CIFAR100, ImageNet100AA robust accuracy (%): CIFAR10 50.27 to 51.37 (λ=1); CIFAR100 38.03 to 39.75 (λ=0.1); ImageNet100 46.74 to 48.82 (λ=0.1)Helped
large nuclear norm regularization weight (λ=3) (ablation)Fast-EG-l1 + nuclear norm · CIFAR10, CIFAR100AA robust accuracy (%): CIFAR10 49.43 and CIFAR100 31.29 at λ=3, below λ=0Hurt
use coordinate descent with small K (K-hot SLIDE) instead of larger K (ablation)10-step SLIDE adversarial training · CIFAR10 (ϵ=12)AA-free robust accuracy of best checkpoint (%): catastrophic overfitting at small K; e.g. best 27.70 at K=... with step 6.0 and K=20 vs 53.47 at K=100 with step 4.5Hurt
existing one-step fast AT methods (FreeAT, FGSM-RS, AdaAT, Grad-Align, N-FGSM, ATTA) with small K (ablation)one-step l1 adversarial training with coordinate descent · CIFAR10 (ϵ=12)robust accuracy (%): all suffer catastrophic overfitting at small K; best robust accuracies remain below SLIDEHurt
step size α=√ϵ in Fast-EG-l1 vs 0.5√ϵ, 0.75√ϵ, 1.25√ϵ (ablation)Fast-EG-l1 · CIFAR10 across ϵ 3 to 24AA robust accuracy (%): performance comparable across step sizes close to √ϵNo clear effect

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