Information and Communications Technology and Policy

Information and Communications Technology and Policy

Information and Communications Technology and Policy ›› 2021, Vol. 47 ›› Issue (6): 27-37.doi: 10.12267/j.issn.2096-5931.2021.06.004

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Key technology and innovation of privacy preserving computing

FU Fangcheng1,2, HOU Chen1,2, CHENG Yong2, TAO Yangyu2   

  1. 1. Department of Computer Science & Key Lab of High Confidence Software Technologies (MOE), Peking University,
    Beijing 100871, China;
    2. Department of Data Platform, TEG, Tencent Inc. , Beijing 100083, China
  • Online:2021-06-15 Published:2021-07-15

Abstract: Big Data has become one of the factors of production and a strategic resource in the digital economy.However, data are usually scattered in different organizations and cannot be integrated in a centralized manner due to privacy concerns in practice, hindering the performance of many real-world big data applications. In order to tackle this problem, privacy preserving computing has been developed to enable the application of data from different parties for federated learning and analysis with privacy guarantees. In this paper, we provide a survey of the key techniques and advances in privacy preserving computing, including private set intersection, diagonal federated learning, asynchronous parallel computation, message compression protocols, unidirectional connections, trusted execution environments, and federated data analysis. Finally, we introduce the applications and techniques in Angel PowerFL, which is a general and industry-grade privacy preserving computing platform.

Key words: privacy preserving computing, federated learning, federated data analysis, Angel PowerFL