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.

Membership Inference Attack against Graph Neural Networks

Related tags

Overview

MIA GNN Project Starter

MIA Attack Process

Training Target and Shadow Model by GCN model

TUs: DD, PROTEINS_full, ENZYMES

SPs: CIFAR10, MNIST

Membership Inference Attack

Acknowledge

Owner

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