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GitHub Repository: https://github.com/manuj-mishra/zkdiffpriv

Delta Z is the first Zero Knowledge Differential Privacy (ZKDP) protocol.

In 2009, Netflix identified an opportunity to share their customer database with the ML community to improve their recommender engine. All data was pseudoanonymous yet hackers were able to reconstruct private information about individuals using statistical methods. 

Clearly, pseudoanonymity is flawed.

Differential privacy provides mathematical guarantees that no personal information can ever be reconstructed from query results. However, it relies on a trusted data curator which is a single point-of-failure for corruption in a way that users are none-the-wiser.

Delta Z is a completely trustless DP solution. We have have implemented key algorithms from differential privacy literature as a Cairo-based smart contracts deployed on StarkNet (goerli). This allows users to submit queries as normal but receive results with verifiably correct noise that doesn't hinder their analysis.

Architecture Diagram:

Differential Privacy summarised in one image: