https://github.com/shreya-28/Secure-ML
Secure Linear Regression in the Semi-Honest Two-Party Setting.
https://github.com/shreya-28/Secure-ML
linear-regression privacy-preserving-machine-learning secure-ml secure-multi-party-computation
Last synced: about 2 months ago
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Secure Linear Regression in the Semi-Honest Two-Party Setting.
- Host: GitHub
- URL: https://github.com/shreya-28/Secure-ML
- Owner: shreya-28
- Created: 2019-10-01T16:59:00.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2019-10-01T18:59:09.000Z (over 6 years ago)
- Last Synced: 2024-04-18T16:02:24.285Z (almost 2 years ago)
- Topics: linear-regression, privacy-preserving-machine-learning, secure-ml, secure-multi-party-computation
- Language: C++
- Homepage:
- Size: 11 MB
- Stars: 34
- Watchers: 1
- Forks: 9
- Open Issues: 2
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-machine-learning-interpretability - Secure-ML -  | "Secure Linear Regression in the Semi-Honest Two-Party Setting." | (Technical Resources / Open Source/Access Responsible AI Software Packages)
README
# Secure Machine Learning
Secure Linear Regression in the Semi-Honest Two-Party Setting. More details on the protocol can be found in the [SecureML paper](https://eprint.iacr.org/2017/396.pdf).
### Prerequisites
1. [emp-ot](https://github.com/emp-toolkit/emp-ot/tree/15fb731e528974bcfe5aa09c18bb16376e949283).
2. [Eigen 3.3.7](http://eigen.tuxfamily.org/index.php?title=Main_Page#Download).
### Building Secure-ML
```
git clone https://github.com/shreya-28/Secure-ML.git
cd Secure-ML
mkdir build
cd build
cmake ..
make
```
### Running Secure-ML
The build system creates two binaries, namely, `ideal_functionality` and `secure_ML`. The former represents the functionality that the latter implements securely.
The binaries can be executed as follows:
* `ideal_functionality`
- `./build/bin/ideal_functionality [num_iter]`
- `secure_ML`
- On local machine
- `./build/bin/secure_ML 1 8000 [num_iter] & ./build/bin/secure_ML 2 8000 [num_iter]`
- On two different machines
- `./build/bin/secure_ML 1 8000 [num_iter]` on Machine 1
- `./build/bin/secure_ML 2 8000 [num_iter] [addr_of_machine_1]` on Machine 2