36 Open source projects that are alternatives of or similar to awesome-machine-learning-reliability

Scaleable input gradient regularization

A Closer Look at Accuracy vs. Robustness

Task-agnostic universal black-box attacks on computer vision neural network via procedural noise (CCS'19)

Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

[ICML 2021] A fast algorithm for fitting robust decision trees. http://proceedings.mlr.press/v139/vos21a.html

Adversarial Attacks on Deep Neural Networks for Time Series Classification

Feature Scattering Adversarial Training

Code for our CVPR 2018 paper, "On the Robustness of Semantic Segmentation Models to Adversarial Attacks"

Code implementation of the paper "With Great Training Comes Great Vulnerability: Practical Attacks against Transfer Learning", at USENIX Security 2018

Source code for the ICLR 2021 work "Generating Adversarial Computer Programs using Optimized Obfuscations"

Code to reproduce the attacks and defenses for the entries "JeromeR" in the NIPS 2018 Adversarial Vision Challenge

The goal of this survey is two-fold: (i) to present recent advances on adversarial machine learning (AML) for the security of RS (i.e., attacking and defense recommendation models), (ii) to show another successful application of AML in generative adversarial networks (GANs) for generative applications, thanks to their ability for learning (high-…

adversarial examples, adversarial malware examples, adversarial malware detection, adversarial deep ensemble, Android malware variants

Attacking Vision based Perception in End-to-end Autonomous Driving Models

[ICML 2019, 20 min long talk] Robust Decision Trees Against Adversarial Examples

Code for the paper: Adversarial Training Against Location-Optimized Adversarial Patches. ECCV-W 2020.

reproduction of Thermometer Encoding: One Hot Way To Resist Adversarial Examples in pytorch

Athena: A Framework for Defending Machine Learning Systems Against Adversarial Attacks

Provably defending pretrained classifiers including the Azure, Google, AWS, and Clarifai APIs

Randomized Smoothing of All Shapes and Sizes (ICML 2020).

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

Robustness benchmark for DNN models.

Code for the unrestricted adversarial examples paper (NeurIPS 2018)

Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)

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

Implemention of Fast Gradient Sign Method for generating adversarial examples in Keras

EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples

Fawkes, privacy preserving tool against facial recognition systems. More info at https://sandlab.cs.uchicago.edu/fawkes

Adversarial Ranking Attack and Defense, ECCV, 2020.

This is our official implementation for the paper: Jinhui Tang, Xiaoyu Du, Xiangnan He, Fajie Yuan, Qi Tian, and Tat-Seng Chua, Adversarial Training Towards Robust Multimedia Recommender System.

Adversarial Distributional Training (NeurIPS 2020)

Backdoors Framework for Deep Learning and Federated Learning. A light-weight tool to conduct your research on backdoors.

A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX

Paper list of Adversarial Examples

Pre-trained model, code, and materials from the paper "Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation" (MICCAI 2019).

NIPS Adversarial Vision Challenge