zkml demo
Private quantized linear regression on Ethereum.
This is a demo of the zkml protocol, which implements a zk-SNARK circuit where the proof verifies that a private model has a certain accuracy under a public dataset, as well as the public encrypted model is exactly the private model encrypted using the shared key.
Presentation: https://www.loom.com/share/fdbe451385dd4a22b5593bf80747a4be
Running
- download
powersOfTau28_hez_final_18.ptau
from circom and move tocircuits
mkdir artifacts && mkdir artifacts/lr
to store artifactscd circuits && yarn prod
to build the circuitscd eth && yarn compile && yarn deploy-{NETWORK}
to deploy the contracts- set up Infura IPFS with
keys/ipfs.json
containing{"id": ..., "secret": ...}
export PRIVATE_KEY=... && export URL=...
to export private key and RPC URL- for the jupyter demo, run
jupyter kernelspec list
to findkernel.json
and add an"env": {"PRIVATE_KEY": ..., "URL": ...}
entry ./zkml
to interact with cli (xDai)
Check it out on-chain
There is an outstanding 20 xDai bounty on the contract, available for claim as of December 2021.
https://blockscout.com/xdai/mainnet/address/0x5B54f06991871cd7EAE76a3D270D9EFFBdC01207/contracts
Protocol Overview
Special Thanks
- ETH Summer
- Lattice