A curated collection of adversarial attack and defense on graph data.
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Updated
Nov 7, 2023 - Python
A curated collection of adversarial attack and defense on graph data.
TransferAttack is a pytorch framework to boost the adversarial transferability for image classification.
[CVPR 2021] Official repository for "Prototype-supervised Adversarial Network for Targeted Attack of Deep Hashing"
Official implementation of CVPR2020 Paper "Cooling-Shrinking Attack"
Bluff: Interactively Deciphering Adversarial Attacks on Deep Neural Networks
[NeurIPS'20] Learning Black-Box Attackers with Transferable Priors and Query Feedback
[NeurIPS-2023] Annual Conference on Neural Information Processing Systems
[SIGIR 2021] Official repository for "Targeted Attack and Defense for Deep Hashing"
vanilla training and adversarial training in PyTorch
From Gradient Leakage to Adversarial Attacks in Federated Learning
Set-level Guidance Attack: Boosting Adversarial Transferability of Vision-Language Pre-training Models. [ICCV 2023 Oral]
Gaussian process regression-based adversarial image detection
[TMM 2022] Official repository for "Targeted Attack of Deep Hashing via Prototype-supervised Adversarial Networks"
SAGA: Spectral Adversarial Geometric Attack on 3D Meshes (ICCV 2023)
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.
Repository of the TSFool method proposed in paper "TSFool: Crafting Highly-Imperceptible Adversarial Time Series through Multi-Objective Attack".
An adversarial image generator
Simple code related to adversarial examples, attacks, and defenses.
[MICCAI 2023] Official code repository of paper titled "Frequency Domain Adversarial Training for Robust Volumetric Medical Segmentation" accepted in MICCAI 2023 conference.
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