Data augmentation for NLP

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.

A Toolbox for Adversarial Robustness Research

An Open-Source Package for Textual Adversarial Attack.

A Harder ImageNet Test Set (CVPR 2021)

Pytorch implementation of convolutional neural network adversarial attack techniques

Simple pytorch implementation of FGSM and I-FGSM

A non-targeted adversarial attack method, which won the first place in NIPS 2017 non-targeted adversarial attacks competition

Official TensorFlow Implementation of Adversarial Training for Free! which trains robust models at no extra cost compared to natural training.

Tensorflow Implementation of Adversarial Attack to Capsule Networks

PyTorch library for adversarial attack and training

Generative Adversarial Perturbations (CVPR 2018)

Code for the CVPR 2019 article "Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses"

A targeted adversarial attack method, which won the NIPS 2017 targeted adversarial attacks competition

A Paperlist of Adversarial Attack on Object Detection

List of state of the art papers, code, and other resources

Spatially Transformed Adversarial Examples with TensorFlow

My entry for ICLR 2018 Reproducibility Challenge for paper Synthesizing robust adversarial examples https://openreview.net/pdf?id=BJDH5M-AW

Deflecting Adversarial Attacks with Pixel Deflection

Project page for our paper: Interpreting Adversarially Trained Convolutional Neural Networks