Digital Identity, Trust and Privacy on the open Internet

New Principles for Privacy-Preserving Queries for Distributed Data

without comments

Here are the three (3) principles for privacy-preserving computation based on the Enigma P2P distributed multi-party computation model:

(a) Bring the Query to the Data: The current model is for the querier to fetch copies of all the data-sets from the distributed nodes, then import the data-sets into the big data processing infra and then run queries. Instead, break-up the query into components (sub-queries) and send the query pieces to the corresponding nodes on the P2P network.

(b) Keep Data Local: Never let raw data leave the node. Raw data must never leaves its physical location or the control of its owner. Instead, nodes that carry relevant data-sets execute sub-queries and report on the result.

(c) Never Decrypt Data: Homomorphic encryption remains an open field of study. However, certain types of queries can be decomposed into rudimentary operations (such as additions and multiplications) on encrypted data that would yield equivalent answers to the case where the query was run on plaintext data.


Written by thomas

August 30th, 2015 at 5:51 pm