PyTorch implementation of adversarial attacks [torchattacks]

Fine-tuned resnet34 and mobilenetv2 on the caltech101 dataset. Tested FGSM attacks and used XAI techniques to understand both models behaviours then implemented two defensive measures against the attacks.

Improvising adversarial attack against prediction of neural network

No description available

A utility project for training adverserial, non-adverserail models, and testing for robustness using torchattacks.

ViTとCNNの内部挙動を敵対的サンプル下で比較する実験用リポジトリ（PyTorch・Hydra・Tiny-ImageNet・torchattacks対応）

A comparative study of the Fast Gradient Sign Method (FGSM) adversarial attack using multiple libraries (Foolbox, CleverHans, Torchattacks, ART) on the CIFAR-10 dataset, highlighting differences in implementation and attack success rates.

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.