Blockchain-assisted Verifiable Secure Multi-Party Data Computing

Abstract

Secure multi-party computation (SMPC) is a crucial technology that supports privacy preservation, enabling multiple users to perform computations on any function without disclosing their private inputs and outputs in a distrustful environment. Existing secure multi-party computation models typically rely on obfuscation circuits and cryptographic protocols to facilitate collaborative computation of tasks. However, the efficiency and privacy leakage of users have not been paid much attention during the computation process. To address these problems, this article proposes a privacy-preserving approach Blockchain-assisted Verifiable Secure Multi-Party Data Computing (BVS-MPDC). Specifically, to prevent privacy leakage when users and multiple participants share data, BVS-MPDC uses additive homomorphic encryption to encrypt data shares; and verifies the generated Pedersen commitment of all the data. BVS-MPDC utilizes an improved Schnorr aggregation signature to improve computation efficiency between computing nodes and smart contracts by submitting an aggregation signature to the blockchain. Moreover, we design and implement a smart contract for verifying aggregation signature results on Ethereum. The security proof is presented under the UC framework. Finally, simulation experiments of performance evaluations demonstrate that our scheme outperforms existing schemes in computation overhead and verification.