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SMS

Self-Supervised Model Seeding (SMS) Scheme for Unlearning Verification

Overview

This repository is the official implementation of SMS, and the corresponding paper is under review.

Prerequisites

python = 3.8.17
pytorch = 2.0.0
matplotlib
numpy
...

Running the experiments

  1. To run the SMS on MNIST
python /VMU/Verifiable_MU/On_MNIST/VMU_on_MNIST.py 
  1. To run the MIB on MNIST
python /VMU/Verifiable_MU/On_MNIST/Membership_inf_via_backdoor/MIB_on_MNIST.py 
  1. To run the SMS on CIFAR10
python /VMU/Verifiable_MU/On_CIFAR10/VMU_on_CIFAR10.py 
  1. To run the MIB on CIFAR10
python /VMU/Verifiable_MU/On_CIFAR10/Membership_inf_via_backdoor/MIB_on_CIFAR10.py
  1. To run the SMS on CIFAR100
python /VMU/Verifiable_MU/On_CIFAR100/VMU_on_CIFAR100.py 
  1. To run the SMS on CelebA
python /VMU/Verifiable_MU/On_CelebA/VMU_on_CelebA32.py 
  1. To run the MIB on CelebA
python /VMU/Verifiable_MU/On_CelebA/MIB_method/MIB_on_CelebA.py

CelebA, MSR=0.6%

Learning Verification Non-Verif. MIB SMS
Model Acc. 97.22% 97.20% 97.28%
Verifiability - 93.27% 95.38%
Unambiguity - 57.38% 90.77%
Running time (s) 3015 3421 4225
Unlearning Verification Non-Verif. MIB SMS
Model Acc. 97.15% 97.17% 97.26%
Verifiability - 100% 3.41%
Unambiguity - 53.72% 98.21%

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