Secure multi-party computation (also known as secure computation, multi-party computation (MPC), or privacy-preserving computation) is a subfield of cryptography with the goal of creating methods for parties to jointly compute a function over their inputs while keeping those inputs private.

FBPCS (Facebook Private Computation Service) is a secure, privacy safe and scalable architecture to deploy MPC (Multi Party Computation) applications in a distributed way on virtual private clouds. FBPCF (Facebook Private Computation Framework) is for scaling MPC computation up via threading, while FBPCS is for scaling MPC computation out via Private Scaling architecture. FBPCS consists of various services, interfaces that enalbe various private measurement solutions, e.g. Private Lift.

Private Scaling resembles the map/reduce architecture and is secure against a semi-honest adversary who tries to learn the inputs of the computation. The goal is to secure the intermediate output of each shard to prevent potential privacy leak.

• An AWS account (Access Key ID, Secret Access Key) to use AWS SDK (boto3 API) in FBPCS
• python >= 3.8
• python3-pip

• python3.8

sudo apt-get install -y python3.8

• python3-pip

sudo apt-get install -y python3-pip

python3.8 -m pip install 'git+https://github.com/facebookresearch/FBPCS.git'
# (add --user if you don't have permission)

# Or, to install it from a local clone:
git clone https://github.com/facebookresearch/FBPCS.git
python3.8 -m pip install -e FBPCS
# (add --user if you don't have permission)

# Or, to install it from Pypi
python3.8 -m pip install fbpcs

• MPCService is the public interface that provides APIs to distribute a MPC application with large dataset to multiple MPC workers on cloud.

• Website: https://github.com/facebookresearch/fbpcs
• See the CONTRIBUTING file for how to help out.

FBPCS is MIT licensed, as found in the LICENSE file.