64 Open source projects that are alternatives of or similar to ijcnn19attacks

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

Paper list of Adversarial Examples

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

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

Code for the unrestricted adversarial examples paper (NeurIPS 2018)

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

Multi-variate time series classification with a bi-directional ESN with a readout implemented as a deep neural network.

Different deep learning architectures are implemented for time series classification and prediction purposes.

My Experiments with Time Series

A pytorch implementation of "Towards Deep Learning Models Resistant to Adversarial Attacks"

Attacking Optical Flow (ICCV 2019)

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

No description or website provided.

CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.

A machine learning toolkit dedicated to time-series data

Python toolbox to evaluate graph vulnerability and robustness (CIKM 2021)

Resources for working with time series and sequence data

Multiple pooling operators and transformations for fast and effective time series classification

KitanaQA: Adversarial training and data augmentation for neural question-answering models

Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks

A curated list of awesome resources regarding machine learning reliability.

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

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

[EMNLP 2020] "T3: Tree-Autoencoder Constrained Adversarial Text Generation for Targeted Attack" by Boxin Wang, Hengzhi Pei, Boyuan Pan, Qian Chen, Shuohang Wang, Bo Li

[ICCV2021 Oral] Fooling LiDAR by Attacking GPS Trajectory

An Algorithm to Quantify Robustness of Recurrent Neural Networks

Code for the paper "Addressing Model Vulnerability to Distributional Shifts over Image Transformation Sets", ICCV 2019

Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"

TrojanZoo provides a universal pytorch platform to conduct security researches (especially backdoor attacks/defenses) of image classification in deep learning.

Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph Machine Learning.

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-…

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

Natural Language Attacks in a Hard Label Black Box Setting.

A unified framework for machine learning with time series

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

Analyzes chronological patterns present in time-series data and provides human-readable descriptions

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

PyTorch implementation of the model presented in "Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention"

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

Adversarial Ranking Attack and Defense, ECCV, 2020.

Robust Out-of-distribution Detection in Neural Networks

Code for the AAAI 2022 publication "Well-classified Examples are Underestimated in Classification with Deep Neural Networks"

A Closer Look at Accuracy vs. Robustness

NIPS Adversarial Vision Challenge

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

Scaleable input gradient regularization

Codes for NeurIPS 2020 paper "Adversarial Weight Perturbation Helps Robust Generalization"

Data augmentation for NLP

AdvPC: Transferable Adversarial Perturbations on 3D Point Clouds (ECCV 2020)

Square Attack: a query-efficient black-box adversarial attack via random search [ECCV 2020]

MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification

Python tools for analyzing the robustness properties of neural networks (NNs) from MIT ACL

Geometric Adversarial Attacks and Defenses on 3D Point Clouds (3DV 2021)

Source code and dataset for the CCKS201 paper "On Robustness and Bias Analysis of BERT-based Relation Extraction"

Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"

This is a collection of algorithms and approaches used in the book adversarial deep learning

"GAN 인 액션"(한빛미디어, 2020)의 코드 저장소입니다.

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

A PyTorch implementation of the Light Temporal Attention Encoder (L-TAE) for satellite image time series. classification

Deep Neural Network Ensembles for Time Series Classification