Skip to content

An implementation of Secure Aggregation algorithm based on "Practical Secure Aggregation for Privacy-Preserving Machine Learning (Bonawitz et. al)" in Python.

Notifications You must be signed in to change notification settings

ammartahir24/SecureAggregation

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

20 Commits
 
 
 
 
 
 

Repository files navigation

SecureAggregation

An implementation of Secure Aggregation algorithm based on "Practical Secure Aggregation for Privacy-Preserving Machine Learning (Bonawitz et. al)" in Python.

Dependencies: Flask, socketio and socketIO_client

pip install Flask

pip install socketio

pip install socketIO-client

Usage:

Client side:

Init:

c = secaggclient(host,port)

Give weights needed to be transmitted (originally set to zero)

c.set_weights(nd_numpyarray,dimensions_of_array)

Set common base and mod

c.configure(common_base, common_mod)

start client side:

c.start()

Server side:

init:

s = secaggserver(host,port,n,k)

where n is number of selected clients for the round and k is number of client responses required before aggregation process begins

start server side:

s.start()

About

An implementation of Secure Aggregation algorithm based on "Practical Secure Aggregation for Privacy-Preserving Machine Learning (Bonawitz et. al)" in Python.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages