Search Results for author:
Found 4 papers, 1 papers with code
Adversarial example soups: averaging multiple adversarial examples improves transferability without increasing additional generation time
For transfer-based attacks, the adversarial examples are crafted on the surrogate model, which can be implemented to mislead the target model effectively.
Adversarial example generation with AdaBelief Optimizer and Crop Invariance
ABI-FGM and CIM can be readily integrated to build a strong gradient-based attack to further boost the success rates of adversarial examples for black-box attacks.
Random Transformation of Image Brightness for Adversarial Attack
Before deep neural networks are deployed, adversarial attacks can thus be an important method to evaluate and select robust models in safety-critical applications.
Boosting Adversarial Attacks on Neural Networks with Better Optimizer
However, the success rate of adversarial attacks can be further improved in black-box environments.
