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Block-SMPC: A Blockchain-based Secure Multi-party Computation for Privacy-Protected Data Sharing - 2020

Block-Smpc: A Blockchain-Based Secure Multi-Party Computation For Privacy-Protected Data Sharing

Research Area:  Blockchain Technology

Abstract:

With the rapid development of Internet of Things, the demand of data sharing is not only to ensure the data integrity, but also to protect user-s individual privacy. Secure multi-party computation, as a technology paradigm based on cryptography technology, enables privacy protection in data sharing among multiple parties, while the implement of secure multi-party computation is limited due to the inefficient, complex computation protocol and frequent interaction. Fortunately, the emergence of blockchain technology provides excellent properties of decentralization, verifiability and high reliability for secure multi-party computation. In this paper, we propose a blockchain-based secure multi-party computation architecture for data sharing, where we design an aggregator consortium for data storage, verification and joint computation. Moreover, we introduce a straightforward secure multi-party computation scheme based on homomorphic encryption. In addition, we analyze and discuss this scheme in terms of data security, access flexibility, attack resistance and potential applications.

Keywords:  

Author(s) Name:  Yuhan Yang , Lijun Wei , Jing Wu , Chengnian Long

Journal name:  

Conferrence name:  ICBCT-20: Proceedings of the 2020 The 2nd International Conference on Blockchain Technology

Publisher name:  ACM

DOI:  10.1145/3390566.3391664

Volume Information:  Pages 46–51