adversarial attack and defense tests
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Updated
Jan 19, 2019 - Jupyter Notebook
adversarial attack and defense tests
[NeurIPS'20] Learning Black-Box Attackers with Transferable Priors and Query Feedback
GraphReach : Position-Aware Graph Neural Network using Reachability Estimations, IJCAI'21
A collection of adversarial attacks on various models built using Deep Learning and Deep Metric Learning techniques. Standard datasets are used.
From Gradient Leakage to Adversarial Attacks in Federated Learning
vanilla training and adversarial training in PyTorch
Neural Network Adversarial Attack Method Based on Improved Genetic Algorithm
[TMM 2022] Official repository for "Targeted Attack of Deep Hashing via Prototype-supervised Adversarial Networks"
Official implementation of CVPR2020 Paper "Cooling-Shrinking Attack"
Code to generate and extend the TCAB dataset.
[SIGIR 2021] Official repository for "Targeted Attack and Defense for Deep Hashing"
[CVPR 2021] Official repository for "Prototype-supervised Adversarial Network for Targeted Attack of Deep Hashing"
Jeu de la bataille navale en Python avec simulation d'un joueur adverse
Compose desired image with data such that will cause pretrained models misbehave.
Gaussian process regression-based adversarial image detection
Bluff: Interactively Deciphering Adversarial Attacks on Deep Neural Networks
Repository of the Multi-TSFool method proposed in paper "TSFool: Crafting Highly-Imperceptible Adversarial Time Series through Multi-Objective Attack".
An adversarial image generator
Set-level Guidance Attack: Boosting Adversarial Transferability of Vision-Language Pre-training Models. [ICCV 2023 Oral]
SAGA: Spectral Adversarial Geometric Attack on 3D Meshes (ICCV 2023)
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