MPC - improve user data privacy in your apps

MultiPartyComputation evolved quite fast to propose new techniques to share private data in common machine learning scripts, to sign messages with cryptographic keys with keys shared on several servers. This powerful but very opaque technology failed to become mainstream because it was so close to primite assembly languages operations, with gates / operations / wires to describe the algorithms, garbled using their logical binary output tables (the binary output being expressed as a return function from binary input gates in a table).

However, recent frameworks tend to propose new approaches to help the developer create secured private frameworks among parties.

One of them is JIFF that is based on Javascript, that would allow mobile to mobile private computation, or even among several browsers. https://multiparty.org/jiff/docs/jsdoc/

Lambda Vision just opened source its MPC compiler (out of golang) that builds garbled circuits from Javascript functions https://github.com/sjehan/JavascriptMPC

Other cryptographic techniques include ZK-SNARKs and FHE (Full Homomorphic Encryption), the latest being yet very computing-incentive (see https://research.aimultiple.com/secure-multi-party-computation/)