Practical Privacy-Preserving K-means Clustering

This is the implementation of our PETS 2020 paper: Practical Privacy-Preserving K-means Clustering(ePrint).

Evaluating on a single server (2 36-cores Intel Xeon CPU E5-2699 v3 @ 2.30GHz and 256GB of RAM) with a single thread per party, our scheme requires 18 minutes to cluster 100,000 data samples into 2 groups.

Installations

Clone project

git clone --recursive git@github.com:osu-crypto/secure-kmean-clustering.git

Required libraries

C++ compiler with C++14 support. There are several library dependencies including Boost, Miracl, libOTe, and Ivory-Runtime. For libOTe, it requires CPU supporting PCLMUL, AES-NI, and SSE4.1. Optional: nasm for improved SHA1 performance. Our code has been tested on both Windows (Microsoft Visual Studio) and Linux. To install the required libraries:

For building boost, miracl and libOTe, please follow the more instructions at libOTe. A quick try for linux: cd libOTe/cryptoTools/thirdparty/linux/, bash all.get, cd back to libOTe, cmake . and then make -j
For Ivory-Runtime, cd Ivory-Runtime/thirdparty/linux, and bash ./ntl.get. Then, you can run cmake -G"Unix Makefiles" in Ivory-Runtime folder, and then make -j

NOTE: if you meet problem with NTL, try to do the following and read Building and using NTL with GMP. If you see an error message cmd.exe not found, try to install https://www.nasm.us/

Building the Project

After recursively cloning project from git git clone --recursive ,

Windows:

build cryptoTools,libOTe, Ivory-Runtime, libCluster, frontend projects in order.
run frontend project

Linux:

make (requirements: CMake, Make, g++ or similar)
for test: ./bin/frontend.exe

Running the code

1. Unit test:

./bin/frontend.exe -t

2. Simulation:

Using two terminals, (For now, the kmean parameters are hardcoding in the main.cpp file, we will add more flags soon)

On the terminal 1, run:

./bin/frontend -r 0

On the terminal 2, run:

./bin/frontend -r 1

Help

For any questions on building or running the library, please contact Ni Trieu at trieun at oregonstate dot edu

DevJPM / secure-kmean-clustering