This is an unofficial implementation of Secure Aggregation Protocol. The details of the protocol can be found in the original paper: (CCS'17) Practical Secure Aggregation for Privacy-Preserving Machine Learning.

There are two ways to use the Secure Aggregation Protocol.

This is the recommended option, as all entities are independent containers. That is, a real federated learning scenario is simulated in this way.

• Pull base image:

$ docker pull chenjunbao/secureaggregation

• Build docker images for each entity:

$ git clone https://github.com/chen-junbao/secureaggregation.git
$ cd secureaggregation/docker
$ ./scripts/build.sh

• Simulate 100 users and set the waiting time and iteration to 60 seconds and 20, respectively:

$ ./start.sh -u 100 -t 60 -i 20

• Install python libraries:

$ git clone https://github.com/chen-junbao/secureaggregation.git
$ cd secureaggregation
$ pip install -r requirements.txt
$ pip install git+https://github.com/blockstack/secret-sharing

$ python main.py -h

• Simulate 100 users and set the waiting time to 300 seconds:

$ python main.py -u 100 -t 300