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 Python library for adversarial machine learning focusing on benchmarking adversarial robustness.

Implementation of Papers on Adversarial Examples

Detection by Attack: Detecting Adversarial Samples by Undercover Attack

Tensorflow Implementation of Adversarial Attack to Capsule Networks

PyTorch library for adversarial attack and training

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.

Implementation of gradient-based adversarial attack(FGSM,MI-FGSM,PGD)

SHIELD: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression

The first real-world adversarial attack on MTCNN face detetction system to date

Implementation of adversarial training under fast-gradient sign method (FGSM), projected gradient descent (PGD) and CW using Wide-ResNet-28-10 on cifar-10. Sample code is re-usable despite changing the model or dataset.

Detection of network traffic anomalies using unsupervised machine learning

Reproduce multiple adversarial attack methods

Paddle-Adversarial-Toolbox (PAT) is a Python library for Deep Learning Security based on PaddlePaddle.

implement Kervolutional Neural Networks (CVPR, 2019) and compare with CNN under the white box attack

六代兴亡如梦，苒苒惊时月。纵使岁寒途远，此志应难夺。

Adversarial attack generation techniques for CIFAR10 based on Pytorch: L-BFGS, FGSM, I-FGSM, MI-FGSM, DeepFool, C&W, JSMA, ONE-PIXEL, UPSET

Adversarial Attack on 3D U-Net model: Brain Tumour Segmentation.

using adversarial attacks to confuse deep-chicken-terminator 🛡️ 🐔