Membership Inference Attack against Graph Neural Networks

Related tags

Deep LearningMIA-GNN
Overview

MIA GNN Project Starter

If you meet the version mismatch error for Lasagne library, please use following command to upgrade Lasagne library.

pip install --upgrade https://github.com/Lasagne/Lasagne/archive/master.zip

MIA Attack Process

Step1: Training Target Model using Target Dataset
Step2: Training Shadow Model using Shadow Dataset
Step3: Training Attack Model using Posteriors retrieved from Shadow Model

Here, Target Dataset and Shadow Dataset are disjoint.

Training Target and Shadow Model by GCN model

TUs: DD, PROTEINS_full, ENZYMES

# 10: run 10 times ;100:start from 100 epochs; DD : dataset DD
sh run_TUs_target_shadow_training.sh 10 100 DD

SPs: CIFAR10, MNIST

# 10: run 10 times ;100:start from 100 epochs; DD : dataset DD
sh run_SPs_target_shadow_training.sh 10 100 DD

Membership Inference Attack

# For transfer based attack, run 15 times
sh run_transfer_attach.sh 15 

Acknowledge

This project references from benchmarking-gnn and DeeperGCN

If it has any issues, please let me know.

MILK: Machine Learning Toolkit

MILK: MACHINE LEARNING TOOLKIT Machine Learning in Python Milk is a machine learning toolkit in Python. Its focus is on supervised classification with

Luis Pedro Coelho 610 Dec 14, 2022
Pytorch implementation of the Variational Recurrent Neural Network (VRNN).

VariationalRecurrentNeuralNetwork Pytorch implementation of the Variational RNN (VRNN), from A Recurrent Latent Variable Model for Sequential Data. Th

emmanuel 251 Dec 17, 2022
Code for "Universal inference meets random projections: a scalable test for log-concavity"

How to use this repository This repository contains code to replicate the results of "Universal inference meets random projections: a scalable test fo

Robin Dunn 0 Nov 21, 2021
Reference implementation of code generation projects from Facebook AI Research. General toolkit to apply machine learning to code, from dataset creation to model training and evaluation. Comes with pretrained models.

This repository is a toolkit to do machine learning for programming languages. It implements tokenization, dataset preprocessing, model training and m

Facebook Research 408 Jan 01, 2023
TensorFlow Implementation of Unsupervised Cross-Domain Image Generation

Domain Transfer Network (DTN) TensorFlow implementation of Unsupervised Cross-Domain Image Generation. Requirements Python 2.7 TensorFlow 0.12 Pickle

Yunjey Choi 865 Nov 17, 2022
Generate vibrant and detailed images using only text.

CLIP Guided Diffusion From RiversHaveWings. Generate vibrant and detailed images using only text. See captions and more generations in the Gallery See

Clay M. 401 Dec 28, 2022
Code repo for "RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network" (Machine Learning and the Physical Sciences workshop in NeurIPS 2021).

RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network An official PyTorch implementation of the RBSRICNN network as desc

Rao Muhammad Umer 6 Nov 14, 2022
Time Dependent DFT in Tamm-Dancoff Approximation

Density Function Theory Program - kspy-tddft(tda) This is an implementation of Time-Dependent Density Functional Theory(TDDFT) using the Tamm-Dancoff

Peter Borthwick 2 Nov 17, 2022
The source code of CVPR17 'Generative Face Completion'.

GenerativeFaceCompletion Matcaffe implementation of our CVPR17 paper on face completion. In each panel from left to right: original face, masked input

Yijun Li 313 Oct 18, 2022
Vision-Language Pre-training for Image Captioning and Question Answering

VLP This repo hosts the source code for our AAAI2020 work Vision-Language Pre-training (VLP). We have released the pre-trained model on Conceptual Cap

Luowei Zhou 373 Jan 03, 2023
Pytorch domain adaptation package

DomainAdaptation This package is created to tackle the problem of domain shifts when dealing with two domains of different feature distributions. In d

Institute of Computational Perception 7 Oct 22, 2022
YOLOv5🚀 reproduction by Guo Quanhao using PaddlePaddle

YOLOv5-Paddle YOLOv5 🚀 reproduction by Guo Quanhao using PaddlePaddle 支持AutoBatch 支持AutoAnchor 支持GPU Memory 快速开始 使用AIStudio高性能环境快速构建YOLOv5训练(PaddlePa

QuanHao Guo 20 Nov 14, 2022
An evaluation toolkit for voice conversion models.

Voice-conversion-evaluation An evaluation toolkit for voice conversion models. Sample test pair Generate the metadata for evaluating models. The direc

30 Aug 29, 2022
Model Agnostic Interpretability for Multiple Instance Learning

MIL Model Agnostic Interpretability This repo contains the code for "Model Agnostic Interpretability for Multiple Instance Learning". Overview Executa

Joe Early 10 Dec 17, 2022
A Home Assistant custom component for Lobe. Lobe is an AI tool that can classify images.

Lobe This is a Home Assistant custom component for Lobe. Lobe is an AI tool that can classify images. This component lets you easily use an exported m

Kendell R 4 Feb 28, 2022
Python implementation of a live deep learning based age/gender/expression recognizer

TUT live age estimator Python implementation of a live deep learning based age/gender/smile/celebrity twin recognizer. All components use convolutiona

Heikki Huttunen 80 Nov 21, 2022
EASY - Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients.

EASY - Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients. This repository is the official im

Yassir BENDOU 57 Dec 26, 2022
[2021][ICCV][FSNet] Full-Duplex Strategy for Video Object Segmentation

Full-Duplex Strategy for Video Object Segmentation (ICCV, 2021) Authors: Ge-Peng Ji, Keren Fu, Zhe Wu, Deng-Ping Fan*, Jianbing Shen, & Ling Shao This

Daniel-Ji 55 Dec 22, 2022
PIGLeT: Language Grounding Through Neuro-Symbolic Interaction in a 3D World [ACL 2021]

piglet PIGLeT: Language Grounding Through Neuro-Symbolic Interaction in a 3D World [ACL 2021] This repo contains code and data for PIGLeT. If you like

Rowan Zellers 51 Oct 08, 2022
Sequence-tagging using deep learning

Classification using Deep Learning Requirements PyTorch version = 1.9.1+cu111 Python version = 3.8.10 PyTorch-Lightning version = 1.4.9 Huggingface

Vineet Kumar 2 Dec 20, 2022