We are setting up a zero knowledge calculation engine for use within financial markets.
To do this in a privacy preserving way, we need to set up a network that will have:
- Multiple nodes with SGX / Trusted Execution Environments
- Some form of consensus mechanism/remote attestation of the privately run nodes
- Cloud deployement of nodes
The privacy preserving layer will communicate with other components that live outside the network
Calculations will be performed on streaming real-time data (e.g. price changes), so the
system should aim for the lowest possible latency. Performance requirements disqualifies solutions such as those based
on decentralized blockchains, or even private blockchain networks to the extent that they introduce a performance overhead.
Ideally we want to remove any dependency on blockchain/token infrastructure. A variety of open source privacy computing
frameworks are available, with a preference for: (removed by Toogit admin)
The developer should explore the extent to which these frameworks can be configured to meet performance
requirements, and decoupled from blockchains (e.g. Ethereum).
We want it set up securely and connected to our existing infrastructure. We will provide:
- The calculations happening in the nodes
- Data feeds to perform calculations (you will be helping with encrypting just the private data and sending that to the network)
- The Database where the outputs will go
About the recuiterMember since May 20, 2018 Shivam Chowdri
from Waikato, New Zealand