targetted-attacks

Here are 4 public repositories matching this topic...

deepmancer / adversarial-attacks-robustness

Evaluating CNN robustness against various adversarial attacks, including FGSM and PGD.

deep-learning notebook cnn pytorch robustness adversarial-attacks pgd-adversarial-attacks fgsm-attack pgd-attack targetted-attacks

Updated Aug 16, 2024
Jupyter Notebook

ericyoc / cnn_hnn_comparison_analysis_poc

Star

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

quantum-classical adversarial-attacks white-box-attacks hybrid-neural-network targetted-attacks

Updated Sep 4, 2024
Jupyter Notebook

ericyoc / hnn_attack_two_diff_defense_choices_poc

Star

Hybrid neural network model is protected against adversarial attacks using either adversarial training or randomization defense techniques

mnist-dataset quantum-classical adversarial-attacks adversarial-training random-rotation classification-models emnist-dataset white-box-attacks hybrid-neural-network targetted-attacks randomization-defense random-resizing random-cropping combined-randomization compounded-attacks

Updated Sep 4, 2024
Jupyter Notebook

ericyoc / quantinuum-hnn-compound-adv-attack-poc

Star

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.

mnist-dataset quantum-classical adversarial-attacks white-box-attacks hybrid-neural-network quantinuum targetted-attacks compounded-adversarial-attack pytket torchattacks pytket-qiskit

Updated Sep 4, 2024
Jupyter Notebook

Add this topic to your repo

To associate your repository with the targetted-attacks topic, visit your repo's landing page and select "manage topics."

Learn more