P-Chain: Towards privacy-aware smart contract using SMPC

Abstract

Smart contract, as the representative application of blockchain, has recently fueled extensive research interests from both academia and industry. However, with its wide applications, the weaknesses of smart contract have been gradually revealed. The major barrier to the widespread adoption of smart contract involves concerns about on-chain privacy which refers to the details of input/output privacy. To address privacy concerns, we propose in this paper, P-Chain, a privacy-aware framework for smart contracts of permissioned blockchain to protect sensitive data of users based on Secure Multi-party Computation (SMPC). Unlike existing work that suffer several key drawbacks, including introducing a third party who could get the details of the deal, and high overhead for on-chain and off-chain communication, as well as lacking a privacy protection for output data, we enhance the privacy protection for smart contracts system by adding a new secure multi-party computation layer in P-Chain. Through secure multi-party computing, sensitive inputs of smart contracts are divided into multiple sub-inputs and sent to computing participants for operation respectively, which ensures that each participant can only access part of the user’s information. A stochastic strategy based on $(t;n)$ threshold secret sharing to select calculating parties is also been proposed, which makes it difficult for an attacker to aggregate $t$ of $n$ participants for launching a collusive attack. In addition, we propose the output privacy protection method that makes it possible to reach a consensus without the need to know the output. The extensive experimental evaluation and analysis demonstrate that our scheme enjoys the advantages of calculation correctness, input–output privacy as well as anti-collusion.