基于多方安全计算的公共数据融合创新模式研究及应用

doi:10.11959/j.issn.2096-0271.2023073

大数据 ›› 2023, Vol. 9 ›› Issue (6): 15-27.doi: 10.11959/j.issn.2096-0271.2023073

• 专题：大数据安全与隐私计算 • 上一篇下一篇

基于多方安全计算的公共数据融合创新模式研究及应用

金加和¹, 赵程遥¹, 求昊泽², 刘鹏²

¹ 浙江省数据开放融合关键技术研究重点实验室，浙江杭州 310007
² 浙江大学计算机科学与技术学院，浙江杭州 310027

出版日期:2023-11-15 发布日期:2023-11-01
作者简介:金加和（1965- ），男，浙江省数据开放融合关键技术研究重点实验室副主任，浙江省大数据发展中心主任、高级工程师，浙江省政务服务标准化技术委员会副秘书长。主要研究方向为数字政府、数据治理、隐私计算等。
赵程遥（1985- ），男，浙江省数据开放融合关键技术研究重点实验室副主任，浙江省大数据发展中心副主任、高级工程师，浙江省信创、国土空间专家库专家。主要研究方向为数据全生命周期管理、数据安全、数据开发利用等。
求昊泽（2000- ），男，浙江大学计算机科学与技术学院硕士生，主要研究方向为隐私计算。
刘鹏（1993- ），男，浙江大学软件学院硕士生，主要研究方向为隐私计算。
基金资助:
国家重点研发计划资助项目(2022YFF0902700)

Research and application of innovative models for public data integration based on secure multi-party computation

Jiahe JIN¹, Chengyao ZHAO¹, Haoze QIU², Peng LIU²

¹ Zhejiang Provincial Laboratory of Data Integration Technology, Hangzhou 310007, China
² School of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China

Online:2023-11-15 Published:2023-11-01
Supported by:
The National Key Research and Development Program of China(2022YFF0902700)

摘要/Abstract

摘要：

多方安全计算技术已广泛应用于金融、互联网等领域，用于解决“数据孤岛”难题，然而其在公共数据领域的应用尚不成熟。针对公共数据领域提出了基于多方安全计算的公共数据融合创新模式，开发设计了在保护数据安全前提下利用各主体公共数据联合计算的技术架构。该模式通过技术创新突破制度制约，实现数据价值提升和保障数据安全的兼顾。主要分析了模式中多方安全计算核心系统的3个子层：联合计算子结构层、安全关系代数层和多方安全计算基础算子层。此外，还给出了实现公共数据融合创新模式的通用流程，并对公共数据融合创新模式的应用实例进行了阐述，为助力数字中国建设、畅通数据资源大循环提供新模式的借鉴。

关键词: 多方安全计算, 公共数据, 融合创新

Abstract:

Secure multi-party computation is widely used in finance, the Internet, and other fields to solve the problem of ＆quot;data silos＆quot;, but its application in the field of public data is not yet mature.An innovative model for public data integration based on secure multi-party computation was proposed, and a technical architecture for joint computing using public data from different parties while protecting their private information was presented.The model breaks through institutional constraints through technological innovation, achieving a balance between improving data value and ensuring data security.Three sub-layers of the core system of secure multi-party computation in the proposed model, including the joint computation substructure layer, the secure relational algebra layer, and the basic operator layer of secure multi-party computation were mainly analyzed.Additionally, a general process for implementing the innovative model was presented, and the practical application of the innovative model was also discussed.The results of this study provide a new reference for promoting digital China construction and facilitating the flow of data resources.

Key words: secure multi-party computation, public data, innovative integration

中图分类号:

TP399

金加和, 赵程遥, 求昊泽, 刘鹏. 基于多方安全计算的公共数据融合创新模式研究及应用[J]. 大数据, 2023, 9(6): 15-27.

Jiahe JIN, Chengyao ZHAO, Haoze QIU, Peng LIU. Research and application of innovative models for public data integration based on secure multi-party computation[J]. Big Data Research, 2023, 9(6): 15-27.

图/表 7

图1

图2

图3

图4

图5

图6

图7

参考文献 23

[1]	PRABHAKARAN M , SAHAI A . Secure multi-party computation[M]. Amsterdam: IOS Press, 2013.
[2]	BELLARE M , HOANG V T , ROGAWAY P . Foundations of garbled circuits[C]// Proceedings of the 2012 ACM Conference on Computer and Communications Security. New York:ACM, 2012: 784-796.
[3]	LINDELL Y , PINKAS B . A proof of security of Yao’s protocol for two-party computation[J]. Journal of Cryptology, 2009,22(2): 161-188.
[4]	MALKHI D , NISAN N , PINKAS B ,et al. Fairplay-a secure two-party computation system[C]// Proceedings of the 13th conference on USENIX Security Symposium - Volume 13. New York:ACM, 2004:20.
[5]	KOLESNIKOV V , SCHNEIDER T . Improved garbled circuit:free XOR gates and applications[C]// Proceedings of International Colloquium on Automata,Languages,and Programming. Heidelberg:Springer, 2008: 486-498.
[6]	KOLESNIKOV V , SADEGHI A R , SCHNEIDER T . Improved garbled circuit building blocks and applications to auctions and computing minima[C]// Proceedings of International Conference on Cryptology and Network Security. Heidelberg:Springer, 2009: 1-20.
[7]	BEIMEL A . Secret-sharing schemes:a survey[C]// Proceedings of International Conference on Coding and Cryptology. Heidelberg:Springer, 2011: 11-46.
[8]	LIU D , HUANG D , LUO P ,et al. New schemes for sharing points on an elliptic curve[J]. Computers ＆ Mathematics with Applications, 2008,56(6): 1556-1561.
[9]	LIN C L , HARN L . Unconditionally secure multi-secret sharing scheme[C]// Proceedings of 2012 IEEE International Conference on Computer Science and Automation Engineering. Piscataway:IEEE Press, 2012: 169-172.
[10]	RABIN M O . How to exchange secrets with oblivious transfer[J]. IACR Cryptology EPrint Archive, 2005:187.
[11]	ASHAROV G , LINDELL Y , SCHNEIDER T ,et al. More efficient oblivious transfer and extensions for faster secure computation[C]// Proceedings of the 2013 ACM SIGSAC Conference on Computer＆ Communications Security. New York:ACM, 2013: 535-548.
[12]	CHOU T , ORLANDI C . The simplest protocol for oblivious transfer[C]// Proceedings of International Conference on Cryptology and Information Security in Latin America. Cham:Springer, 2015: 40-58.
[13]	GARG S , HAJIABADI M , OSTROVSKY R . Efficient range-trapdoor functions and applications:rate-1 OT and more[C]// Proceedings of Theory of Cryptography Conference. Cham:Springer, 2020: 88-116.
[14]	CRAMER R , DAMG?RD I , NIELSEN J B . Multiparty computation from threshold homomorphic encryption[M]// Lecture notes in computer science. Heidelberg: Springer, 2001: 280-300.
[15]	GENTRY C , BONEH D . A fully homomorphic encryption scheme[M].[S.l.:s.n.], 2009.
[16]	NAEHRIG M , LAUTER K , VAIKUNTANATHAN V . Can homomorphic encryption be practical?[C]// Proceedings of the 3rd ACM workshop on Cloud computing security workshop. New York:ACM, 2011: 113-124.
[17]	CHEN C C , ZHOU J , WANG L ,et al. When homomorphic encryption marries secret sharing:secure large-scale sparse logistic regression and applications in risk control[C]// Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery ＆ Data Mining. New York:ACM, 2021: 2652-2662.
[18]	王云河, 李艺 . MPC金融应用场景[J]. 金融电子化, 2021(2): 20-22.
	WANG Y H , LI Y . Financial application scenarios of secure multi-party computation[J]. Financial Digitization, 2021(2): 20-22.
[19]	张燕, 杨一帆, 伊人 ,等. 隐私计算场景下数据质量治理探索与实践[J]. 大数据, 2022,8(5): 55-73.
	ZHANG Y , YANG Y F , YI R ,et al. Exploration and practice of data quality governance in privacy computing scenarios[J]. Big Data Research, 2022,8(5): 55-73.
[20]	张舒黎, 邓春华, 胡松 ,等. 安全多方计算体系架构及应用思考[J]. 通信技术, 2021,54(9): 2182-2189.
	ZHANG S L , DENG C H , HU S ,et al. System architecture and application thinking of secure multiparty computation[J]. Communications Technology, 2021,54(9): 2182-2189.
[21]	贾轩, 白玉真, 马智华 . 隐私计算应用场景综述[J]. 信息通信技术与政策, 2022(5): 45-52.
	JIA X , BAI Y Z , MA Z H . Overview of privacy preserving computing application scenarios[J]. Information and Communications Technology and Policy, 2022(5): 45-52.
[22]	朱智韬, 司世景, 王健宗 ,等. 联邦推荐系统综述[J]. 大数据, 2022,8(4): 105-132.
	ZHU Z T , SI S J , WANG J Z ,et al. Survey on federated recommendation systems[J]. Big Data Research, 2022,8(4): 105-132.
[23]	HAMADA K , IKARASHI D , CHIDA K ,et al. Oblivious radix sort:an efficient sorting algorithm for practical secure multi-party computation[J]. IACR Cryptology EPrint Archive,2014, 2014:121.

基于多方安全计算的公共数据融合创新模式研究及应用

Research and application of innovative models for public data integration based on secure multi-party computation

在线阅读

PDF下载

可视化

摘要/Abstract

引用本文

使用本文

图/表 7

参考文献 23

相关文章 3

Metrics

推荐阅读 0

[1]	高丰. 厘清公共数据授权运营：定位与内涵[J]. 大数据, 2023, 9(2): 16-32.
[2]	张群, 尹卓, 于浩, 王为中, 贾晓杰. 欧盟开放数据和公共部门信息再利用指令的启示[J]. 大数据, 2022, 8(6): 143-152.
[3]	汪疆平, 肖戎. 税务大数据分析的技术和典型应用[J]. 大数据, 2017, 3(2): 92-103.