Defending against Model Stealing via Verifying Embedded External Features

Overview

Defending against Model Stealing Attacks via Verifying Embedded External Features

This is the official implementation of our paper Defending against Model Stealing Attacks via Verifying Embedded External Features, accepted by the AAAI Conference on Artificial Intelligence (AAAI), 2022. This research project is developed based on Python 3 and Pytorch, created by Yiming Li and Linghui Zhu.

Pipeline

Pipeline

Requirements

To install requirements:

pip install -r requirements.txt

Make sure the directory follows:

stealingverification
├── data
│   ├── cifar10
│   └── ...
├── gradients_set 
│   
├── prob
│   
├── network
│   
├── model
│   ├── victim
│   └── ...
|

Dataset Preparation

Make sure the directory data follows:

data
├── cifar10_seurat_10%
|   ├── train
│   └── test
├── cifar10  
│   ├── train
│   └── test
├── subimage_seurat_10%
│   ├── train
|   ├── val
│   └── test
├── sub-imagenet-20
│   ├── train
|   ├── val
│   └── test

📋 Data Download Link:
data

Model Preparation

Make sure the directory model follows:

model
├── victim
│   ├── vict-wrn28-10.pt
│   └── ...
├── benign
│   ├── benign-wrn28-10.pt
│   └── ...
├── attack
│   ├── atta-label-wrn16-1.pt
│   └── ...
└── clf

📋 Model Download Link:
model

Collecting Gradient Vectors

Collect gradient vectors of victim and benign model with respect to transformed images.

CIFAR-10:

python gradientset.py --model=wrn16-1 --m=./model/victim/vict-wrn16-1.pt --dataset=cifar10 --gpu=0
python gradientset.py --model=wrn28-10 --m=./model/victim/vict-wrn28-10.pt --dataset=cifar10 --gpu=0
python gradientset.py --model=wrn16-1 --m=./model/benign/benign-wrn16-1.pt --dataset=cifar10 --gpu=0
python gradientset.py --model=wrn28-10 --m=./model/benign/benign-wrn28-10.pt --dataset=cifar10 --gpu=0

ImageNet:

python gradientset.py --model=resnet34-imgnet --m=./model/victim/vict-imgnet-resnet34.pt --dataset=imagenet --gpu=0
python gradientset.py --model=resnet18-imgnet --m=./model/victim/vict-imgnet-resnet18.pt --dataset=imagenet --gpu=0
python gradientset.py --model=resnet34-imgnet --m=./model/benign/benign-imgnet-resnet34.pt --dataset=imagenet --gpu=0
python gradientset.py --model=resnet18-imgnet --m=./model/benign/benign-imgnet-resnet18.pt --dataset=imagenet --gpu=0

Training Ownership Meta-Classifier

To train the ownership meta-classifier in the paper, run these commands:

CIFAR-10:

python train_clf.py --type=wrn28-10 --dataset=cifar10 --gpu=0
python train_clf.py --type=wrn16-1 --dataset=cifar10 --gpu=0

ImageNet:

python train_clf.py --type=resnet34-imgnet --dataset=imagenet --gpu=0
python train_clf.py --type=resnet18-imgnet --dataset=imagenet --gpu=0

Ownership Verification

To verify the ownership of the suspicious models, run this command:

CIFAR-10:

python ownership_verification.py --mode=source --dataset=cifar10 --gpu=0 

#mode: ['source','distillation','zero-shot','fine-tune','label-query','logit-query','benign']

ImageNet:

python ownership_verification.py --mode=logit-query --dataset=imagenet --gpu=0 

#mode: ['source','distillation','zero-shot','fine-tune','label-query','logit-query','benign']

An Example of the Result

python ownership_verification.py --mode=fine-tune --dataset=cifar10 --gpu=0 

result:  p-val: 1.9594572166549425e-08 mu: 0.47074130177497864

Reference

If our work or this repo is useful for your research, please cite our paper as follows:

@inproceedings{li2022defending,
  title={Defending against Model Stealing via Verifying Embedded External Features},
  author={Li, Yiming and Zhu, Linghui and Jia, Xiaojun and Jiang, Yong and Xia, Shu-Tao and Cao, Xiaochun},
  booktitle={AAAI},
  year={2022}
}
A repository that finds a person who looks like you by using face recognition technology.

Find Your Twin Hello everyone, I've always wondered how casting agencies do the casting for a scene where a certain actor is young or old for a movie

Cengizhan Yurdakul 3 Jan 29, 2022
Cross-Task Consistency Learning Framework for Multi-Task Learning

Cross-Task Consistency Learning Framework for Multi-Task Learning Tested on numpy(v1.19.1) opencv-python(v4.4.0.42) torch(v1.7.0) torchvision(v0.8.0)

Aki Nakano 2 Jan 08, 2022
Crawl & visualize ICLR papers and reviews

Crawl and Visualize ICLR 2022 OpenReview Data Descriptions This Jupyter Notebook contains the data crawled from ICLR 2022 OpenReview webpages and thei

Federico Berto 75 Dec 05, 2022
Pytorch implementation AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks

AttnGAN Pytorch implementation for reproducing AttnGAN results in the paper AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative

Tao Xu 1.2k Dec 26, 2022
How to use TensorLayer

How to use TensorLayer While research in Deep Learning continues to improve the world, we use a bunch of tricks to implement algorithms with TensorLay

zhangrui 349 Dec 07, 2022
Controlling a game using mediapipe hand tracking

These scripts use the Google mediapipe hand tracking solution in combination with a webcam in order to send game instructions to a racing game. It features 2 methods of control

3 May 17, 2022
Official PyTorch implementation of Joint Object Detection and Multi-Object Tracking with Graph Neural Networks

This is the official PyTorch implementation of our paper: "Joint Object Detection and Multi-Object Tracking with Graph Neural Networks". Our project website and video demos are here.

Richard Wang 443 Dec 06, 2022
Gradient Step Denoiser for convergent Plug-and-Play

Source code for the paper "Gradient Step Denoiser for convergent Plug-and-Play"

Samuel Hurault 11 Sep 17, 2022
Unofficial JAX implementations of Deep Learning models

JAX Models Table of Contents About The Project Getting Started Prerequisites Installation Usage Contributing License Contact About The Project The JAX

107 Jan 05, 2023
Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight)

Learning to Adapt Structured Output Space for Semantic Segmentation Pytorch implementation of our method for adapting semantic segmentation from the s

Yi-Hsuan Tsai 782 Dec 30, 2022
Third party Pytorch implement of Image Processing Transformer (Pre-Trained Image Processing Transformer arXiv:2012.00364v2)

ImageProcessingTransformer Third party Pytorch implement of Image Processing Transformer (Pre-Trained Image Processing Transformer arXiv:2012.00364v2)

61 Jan 01, 2023
Camview - A CLI-tool used to stream CCTV online footage based on URL params

CamView A CLI-tool used to stream CCTV online footage based on URL params Get St

Finn Lancaster 54 Dec 09, 2022
ByteTrack(Multi-Object Tracking by Associating Every Detection Box)のPythonでのONNX推論サンプル

ByteTrack-ONNX-Sample ByteTrack(Multi-Object Tracking by Associating Every Detection Box)のPythonでのONNX推論サンプルです。 ONNXに変換したモデルも同梱しています。 変換自体を試したい方はByteT

KazuhitoTakahashi 16 Oct 26, 2022
[ACL 20] Probing Linguistic Features of Sentence-level Representations in Neural Relation Extraction

REval Table of Contents Introduction Overview Requirements Installation Probing Usage Citation License 🎓 Introduction REval is a simple framework for

13 Jan 06, 2023
Automated image registration. Registrationimation was too much of a mouthful.

alignimation Automated image registration. Registrationimation was too much of a mouthful. This repo contains the code used for my blog post Alignimat

Ethan Rosenthal 9 Oct 13, 2022
Code to run experiments in SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression.

Code to run experiments in SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression. Not an official Google product. Me

Google Research 27 Dec 12, 2022
This repository contains the code for TACL2021 paper: SummaC: Re-Visiting NLI-based Models for Inconsistency Detection in Summarization

SummaC: Summary Consistency Detection This repository contains the code for TACL2021 paper: SummaC: Re-Visiting NLI-based Models for Inconsistency Det

Philippe Laban 24 Jan 03, 2023
Calling Julia from Python - an experiment on data loading

Calling Julia from Python - an experiment on data loading See the slides. TLDR After reading Patrick's blog post, we decided to try to replace C++ wit

Abel Siqueira 8 Jun 07, 2022
The official code repository for examples in the O'Reilly book 'Generative Deep Learning'

Generative Deep Learning Teaching Machines to paint, write, compose and play The official code repository for examples in the O'Reilly book 'Generativ

David Foster 1.3k Dec 29, 2022
[ICLR 2021] Is Attention Better Than Matrix Decomposition?

Enjoy-Hamburger 🍔 Official implementation of Hamburger, Is Attention Better Than Matrix Decomposition? (ICLR 2021) Under construction. Introduction T

Gsunshine 271 Dec 29, 2022