Andrea Di Nenno
Incentive-Compatible and Privacy-Preserving Data Analytics System enabled by Blockchain and Multiparty Computation.
Rel. Danilo Bazzanella. Politecnico di Torino, Master of science program in Computer Engineering, 2019
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Abstract
Blockchain, the technology at the foundation of Bitcoin and other cryptocurrencies, is being praised as a major disruptive innovation with the potential to transform most industries. Yet, considering its base architecture, it lacks some fundamental properties that are preventing a larger scale adoption. Among the others, being the blockchain a public and shared ledger, it doesn't offer privacy of data, precluding its usage to many applications that handle sensitive pieces of information. In this work, the blockchain is integrated with Secure Multi-Party Computation (MPC), a cryptographic tool that allows a number of parties to jointly compute a function over their inputs, keeping them private and guaranteeing that the output (if returned) is correct.
Although the two might look apparently distant, they actually address the same set of problems, the ones where mutually mistrusting parties are involved without a trusted third party
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