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.
FBPCP (Facebook Private Computation Platform) 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 FBPCP is for scaling MPC computation out via Private Scaling architecture. FBPCP consists of various services, interfaces that enable 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.
sudo apt-get install -y python3.8
sudo apt-get install -y python3-pip
python3.8 -m pip install 'git+https://github.com/facebookresearch/fbpcp.git'
# (add --user if you don't have permission)
# Or, to install it from a local clone:
git clone https://github.com/facebookresearch/fbpcp.git
python3.8 -m pip install -e fbpcp
# (add --user if you don't have permission)
# Or, to install it from Pypi
python3.8 -m pip install fbpcp
python3.8 -m pip uninstall fbpcp
# uninstall fbpcp first
python3.8 -m pip install 'git+https://github.com/facebookresearch/fbpcp.git'
# (add --user if you don't have permission)
# re-install fbpcp from github repository
python3.8 -m pip install fbpcp --upgrade
FBPCP is MIT licensed, as found in the LICENSE file.
FAQs
Facebook Private Computation Platform
We found that fbpcp demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
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