How can we share data on blockchain networks with enough plausible deniability to give us confidence that we wouldn’t be recognized by the data we share but by giving confidence that the statistics based on the data are not baseless? Yacov Manevich presented our shared paper, “Privacy-Preserving Transactions with Verifiable Local Differential Privacy” by Danielle Movsowitz-Davidow and Eran Toch at the AFT (Advances in Financial Technologies) conference in Princeton, N.J. We present a protocol for Verifiable Differential Privacy on Blockchain Networks that uses zero-knowledge proofs and local differential privacy to achieve an agreed-upon level of noise that can be verified without leaking any data a blockchain user shares.

The full paper can be found here.

And the Github repository code for the library is on ZKAT-VDP.