adversarial-examples
There are 261 repositories under adversarial-examples topic.
Trusted-AI/adversarial-robustness-toolbox
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
dhowe/AdNauseam
AdNauseam: Fight back against advertising surveillance
QData/TextAttack
TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/
bethgelab/foolbox
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
advboxes/AdvBox
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models. Advbox give a command line tool to generate adversarial examples with Zero-Coding.
BorealisAI/advertorch
A Toolbox for Adversarial Robustness Research
DSE-MSU/DeepRobust
A pytorch adversarial library for attack and defense methods on images and graphs
MadryLab/photoguard
Raising the Cost of Malicious AI-Powered Image Editing
airbnb/artificial-adversary
🗣️ Tool to generate adversarial text examples and test machine learning models against them
sarathknv/adversarial-examples-pytorch
Implementation of Papers on Adversarial Examples
ChandlerBang/awesome-graph-attack-papers
Adversarial attacks and defenses on Graph Neural Networks.
Koukyosyumei/AIJack
Security and Privacy Risk Simulator for Machine Learning (arXiv:2312.17667)
hbaniecki/adversarial-explainable-ai
💡 Adversarial attacks on explanations and how to defend them
Verified-Intelligence/auto_LiRPA
auto_LiRPA: An Automatic Linear Relaxation based Perturbation Analysis Library for Neural Networks and General Computational Graphs
chbrian/awesome-adversarial-examples-dl
A curated list of awesome resources for adversarial examples in deep learning
kabkabm/defensegan
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models (published in ICLR2018)
Verified-Intelligence/alpha-beta-CROWN
alpha-beta-CROWN: An Efficient, Scalable and GPU Accelerated Neural Network Verifier (winner of VNN-COMP 2021, 2022, and 2023)
tao-bai/attack-and-defense-methods
A curated list of papers on adversarial machine learning (adversarial examples and defense methods).
ryderling/DEEPSEC
DEEPSEC: A Uniform Platform for Security Analysis of Deep Learning Model
unica-mlsec/mlsec
PhD/MSc course on Machine Learning Security (Univ. Cagliari)
ashafahi/free_adv_train
Official TensorFlow Implementation of Adversarial Training for Free! which trains robust models at no extra cost compared to natural training.
shangtse/robust-physical-attack
Physical adversarial attack for fooling the Faster R-CNN object detector
jeromerony/adversarial-library
Library containing PyTorch implementations of various adversarial attacks and resources
wanglouis49/pytorch-adversarial_box
PyTorch library for adversarial attack and training
ZhengyuZhao/AI-Security-and-Privacy-Events
A curated list of academic events on AI Security & Privacy
gmh14/RobNets
[CVPR 2020] When NAS Meets Robustness: In Search of Robust Architectures against Adversarial Attacks
as791/Adversarial-Example-Attack-and-Defense
This repository contains the implementation of three adversarial example attack methods FGSM, IFGSM, MI-FGSM and one Distillation as defense against all attacks using MNIST dataset.
ZhengyuZhao/TransferAttackEval
Revisiting Transferable Adversarial Images (arXiv)
rfeinman/detecting-adversarial-samples
Code for "Detecting Adversarial Samples from Artifacts" (Feinman et al., 2017)
anuragarnab/adversarial-attacks
Code for our CVPR 2018 paper, "On the Robustness of Semantic Segmentation Models to Adversarial Attacks"
hendrycks/pre-training
Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)
tanjuntao/Adversarial-Machine-Learning
对抗样本（Adversarial Examples）和投毒攻击（Poisoning Attacks）相关资料
microsoft/denoised-smoothing
Provably defending pretrained classifiers including the Azure, Google, AWS, and Clarifai APIs
tml-epfl/understanding-fast-adv-training
Understanding and Improving Fast Adversarial Training [NeurIPS 2020]
huanzhang12/CROWN-IBP
Certified defense to adversarial examples using CROWN and IBP. Also includes GPU implementation of CROWN verification algorithm (in PyTorch).
qilong-zhang/Patch-wise-iterative-attack
Patch-wise iterative attack (accepted by ECCV 2020) to improve the transferability of adversarial examples.