advrankAdversarial Ranking Attack and Defense, ECCV, 2020.
Stars: ✭ 19 (-36.67%)
FeatureScatterFeature Scattering Adversarial Training
Stars: ✭ 64 (+113.33%)
KitanaQAKitanaQA: Adversarial training and data augmentation for neural question-answering models
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ThermometerEncodingreproduction of Thermometer Encoding: One Hot Way To Resist Adversarial Examples in pytorch
Stars: ✭ 15 (-50%)
athenaAthena: A Framework for Defending Machine Learning Systems Against Adversarial Attacks
Stars: ✭ 39 (+30%)
denoised-smoothingProvably defending pretrained classifiers including the Azure, Google, AWS, and Clarifai APIs
Stars: ✭ 82 (+173.33%)
jpeg-defenseSHIELD: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression
Stars: ✭ 82 (+173.33%)
Denoised-Smoothing-TFMinimal implementation of Denoised Smoothing (https://arxiv.org/abs/2003.01908) in TensorFlow.
Stars: ✭ 19 (-36.67%)
EAD AttackEAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples
Stars: ✭ 34 (+13.33%)
Adversarial Robustness ToolboxAdversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
Stars: ✭ 2,638 (+8693.33%)
FawkesFawkes, privacy preserving tool against facial recognition systems. More info at https://sandlab.cs.uchicago.edu/fawkes
Stars: ✭ 4,362 (+14440%)
AMRThis 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.
Stars: ✭ 30 (+0%)
backdoors101Backdoors Framework for Deep Learning and Federated Learning. A light-weight tool to conduct your research on backdoors.
Stars: ✭ 181 (+503.33%)
tulipScaleable input gradient regularization
Stars: ✭ 19 (-36.67%)
translearnCode implementation of the paper "With Great Training Comes Great Vulnerability: Practical Attacks against Transfer Learning", at USENIX Security 2018
Stars: ✭ 18 (-40%)
adversarial-code-generationSource code for the ICLR 2021 work "Generating Adversarial Computer Programs using Optimized Obfuscations"
Stars: ✭ 16 (-46.67%)
adversarial-recommender-systems-surveyThe 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-…
Stars: ✭ 110 (+266.67%)
AdverseDriveAttacking Vision based Perception in End-to-end Autonomous Driving Models
Stars: ✭ 24 (-20%)
procedural-advmlTask-agnostic universal black-box attacks on computer vision neural network via procedural noise (CCS'19)
Stars: ✭ 47 (+56.67%)
domain-shift-robustnessCode for the paper "Addressing Model Vulnerability to Distributional Shifts over Image Transformation Sets", ICCV 2019
Stars: ✭ 22 (-26.67%)
Robust-Semantic-SegmentationDynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation (ICCV2021)
Stars: ✭ 25 (-16.67%)
adanLanguage-Adversarial Training for Cross-Lingual Text Classification (TACL)
Stars: ✭ 60 (+100%)
AdMRLCode for paper "Model-based Adversarial Meta-Reinforcement Learning" (https://arxiv.org/abs/2006.08875)
Stars: ✭ 30 (+0%)
AWPCodes for NeurIPS 2020 paper "Adversarial Weight Perturbation Helps Robust Generalization"
Stars: ✭ 114 (+280%)
CVPR 2019 PNIpytorch implementation of Parametric Noise Injection for adversarial defense
Stars: ✭ 30 (+0%)
sparse-rsSparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks
Stars: ✭ 24 (-20%)