Secure multiparty computation supports machine learning in sensor networks.

The Cicada project is a collaboration between Sandia National Laboratories and the University of New Mexico to develop the necessary foundations for privacy-preserving machine learning in large networks of autonomous drones.  Their approach utilizes secure multiparty communication methods to protect information within decentralized networks of low-power sensors that communicate via radio frequency.  These networks are resilient to the random failure of a small fraction of nodes, remain secure even if an adversary captures a small subset of nodes, and are capable of basic machine learning. This new capability will help address national security priorities such as physical security and command, control, and communications.

A video is available with more information on privacy-preserving machine learning at the Autonomy NM Robotics Lab:  https://www.youtube.com/watch?v=GM_JuKrw4Ik

For more information on the Cicada software package, visit https://cicada-mpc.readthedocs.io

Illustration of privacy-preserving communication over a network of autonomous drones.
Illustration of privacy-preserving communication over a network of autonomous drones.
Contact
Jonathan W. Berry, jberry@sandia.gov

January 1, 2022

News story url: https://www.sandia.gov/ccr/news/secure-multiparty-computation-supports-machine-learning-in-sensor-networks/