dl-model-extraction
Model extraction attack - a Noob's attempt
Science Score: 54.0%
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○Scientific vocabulary similarity
Low similarity (6.3%) to scientific vocabulary
Repository
Model extraction attack - a Noob's attempt
Basic Info
- Host: GitHub
- Owner: dannyrichy
- License: mit
- Language: Jupyter Notebook
- Default Branch: master
- Size: 109 MB
Statistics
- Stars: 1
- Watchers: 1
- Forks: 1
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Model extraction attacks
door.py has the high-level experiment code. The final report for this project can be found here
About
The aim of the project is to analyse model extraction techniques. Furthermore, it analyses how the extracted model can be used to do membership inference attack on the original model. It further explores if such an extracted momdel can be used to perform adversarial attacks on the original model
Experimental setup:
- Victim models for datasets CIFAR-10 and CIFAR-100 were used to carry-out extraction attack analysis. The CIFAR-10 models were taken directly from here. For CIFAR-100, we trained our own models to act as victim.
- Attacker model architecture was varied
- The extraction technique was also run on an Out of Distrbution dataset which we put together from downsampled ImageNet data (32x32). An many-to-one relation between the imagenet class and cifar-10 was prepared. Data for classes Deer and Horse were not found in Imagenet, hence they were downloaded from the internet and downsampled to 32 x 32.
Resources
To help us analyse the performance, we restricted our experiments to CIFAR-10 and CIFAR-100. To emulate the victim model, we used pre-trained models from the following repositories: - https://zenodo.org/record/4431043
References
Data Free Model Extraction: https://arxiv.org/pdf/2011.14779.pdf
Owner
- Name: Daniel Richards R
- Login: dannyrichy
- Kind: user
- Location: Stockholm,Sweden
- Repositories: 1
- Profile: https://github.com/dannyrichy
Msc in Machine Learning
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Ravi Arputharaj"
given-names: "Daniel Richards"
orcid: "https://orcid.org/0000-0000-0000-0000"
- family-names: "Kalaivanan"
given-names: "Adhithyan"
orcid: "https://orcid.org/0000-0000-0000-0000"
- family-names: "Ganesan"
given-names: "Aishwarya"
orcid: "https://orcid.org/0000-0000-0000-0000"
title: "Deep Learning - Model Extraction"
version: 1.0
doi: 10.5281/zenodo.1234
date-released: 2022-05-25
url: "https://github.com/the-nihilist-ninja/dl-model-extraction"
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