Popular GitHub Repositories for White Box Attacks

Sparse and Imperceivable Adversarial Attacks (accepted to ICCV 2019).

A classical or convolutional neural network model with adversarial defense protection

A comparison analysis between classical and quantum-classical (or hybrid) neural network and the impact effectiveness of a compound adversarial attack.

Attack models that are pretrained on ImageNet. (1) Attack single model or multiple models. (2) Apply white-box attacks or black-box attacks. (3) Apply non-targeted attacks or targeted attacks.

BERT based deep neural network for aspect-based sentiment analysis.

Fast Gradient Sign Adversarial Attack(FGSM) examples creation using FashionMnist dataset

PyTorch implementation of ReACG, accepted at ICPRAI 2024.

A quantum-classical (or hybrid) neural network and the use of a adversarial attack mechanism. The core libraries employed are Quantinuum pytket and pytket-qiskit. torchattacks is used for the white-box, targetted, compounded adversarial attacks.

Official implementation of "Appropriate Balance of Diversification and Intensification Improves Performance and Efficiency of Adversarial Attacks", Transactions on Machine Learning Research (TMLR).