An innovative system of data element circulation based on knowledge federation

doi:10.12267/j.issn.2096-5931.2023.06.009

Abstract

Abstract:

With the rapid development of big data and artificial intelligence, how to protect data security has become an urgent problem. Against this backdrop, the privacy-preserving computation technology provides a new circulation mode of data elements. Combined with big data, artificial intelligence and cryptography, an innovative system of data element circulation based on knowledge federation is proposed. It solves the primary business problems faced by the current data element circulation, and the security and privacy problems of different levels of data. In addition, it gives full play to the business value of the data, and realizes quantification, thus creating a virtuous circle of data element circulation through the data value evaluation.

Key words: data element circulation, privacy-preserving computation, knowledge federation, data security

CLC Number:

TN929.11

ZHOU Yijing, CUI Zhuo, HUANG Cuiting, LIN Wenzhen, CHEN Tao. An innovative system of data element circulation based on knowledge federation[J]. Information and Communications Technology and Policy, 2023, 49(6): 61-70.

Add to citation manager EndNote|Ris|BibTeX

URL:

http://ictp.caict.ac.cn/EN/10.12267/j.issn.2096-5931.2023.06.009

http://ictp.caict.ac.cn/EN/Y2023/V49/I6/61

Figures/Tables 8

References 10

[1]	国家工业信息安全发展研究中心. 中国数据要素市场发展报告(2021—2022)[R], 2022.
[2]	EVANS D, KOLESNIKOV V, ROSULEK M. A pragmatic introduction to secure multi-party computation[J]. Foundations & Trends in Privacy & Security, 2018, 2(2-3):70-246.
[3]	YANG Q, LIU Y, CHEN T, et al. Federated machine learning: concept and applications[J]. ACM Transactions on Intelligent Systems and Technology (TIST), 2019, 10(2):1-19.
[4]	SABT M, ACHEMLAL M, BOUABDALLAH A. Trusted execution environment: what it is, and what it is not[C]//IEEE International Conference on Trust, Security and Privacy in Computing and Communications. IEEE, 2015(1):57-64.
[5]	顾冉, 程烨, GU R, 等. 隐私计算技术在数据要素流通领域的探索与实践[C]//姚前, 朱烨东. 中国区块链发展报告(2022). 北京: 社会科学文献出版社, 2022:300-305.
[6]	黄翠婷, 张帆, 孙小超, 等. 隐私集合求交技术的理论与金融实践综述[J]. 信息通信技术与政策, 2021, 47(6):50-56.
[7]	SEBASTIAN A, HAO C, KIM L, et al. PIR with compressed queries and amortized query processing[C]//2018 IEEE symposium on security and privacy (SP). IEEE, 2018: 962-979.
[8]	刘金钊, 汪寿阳. 国际数据要素市场的战略布局我国发展现状与对策探究[EB/OL]. (2022-11-15)[2023-02-16]. http://cn.chinagate.cn/news/2022-11/15/content_78514149.htm
[9]	LI H, MENG D, WANG H, et al. Knowledge federation: a unified and hierarchical privacy-preserving AI framework[C]//2020 IEEE International Conference on Knowledge Graph (ICKG). IEEE, 2020: 84-91.
[10]	LIU Z, CHEN Y, YU H, et al. GTG-Shapley: efficient and accurate participant contribution evaluation in federated learning[J]. ACM Transactions on Intelligent Systems and Technology (TIST), 2022, 13(4): 1-21.

联邦应用	别名	关注重点	联邦阶段
联邦共享	安全多方共享	数据查询检索	信息层
联邦计算	安全多方计算	线性统计分析	信息层
联邦学习	安全多方学习	负责模型训练学习	模型层、认知层
联邦预测	安全多方预测	模型预测使用	信息层、模型层
联邦推理	安全多方推理	知识推理和演绎	认知层、知识层

联邦应用	别名	关注重点	联邦阶段
联邦共享	安全多方共享	数据查询检索	信息层
联邦计算	安全多方计算	线性统计分析	信息层
联邦学习	安全多方学习	负责模型训练学习	模型层、认知层
联邦预测	安全多方预测	模型预测使用	信息层、模型层
联邦推理	安全多方推理	知识推理和演绎	认知层、知识层

[1]	HU Jian, ZHANG Lintao, CHAI Hua, ZHENG Liang, HE Chengfei. Exploration of privacy-preserving computation combined with supercomputing [J]. Information and Communications Technology and Policy, 2023, 49(6): 79-83.
[2]	FANG Jing, ZHOU Yongkai, BIAN Yang, WANG Qi, DING Yadan. Practices and thoughts on privacy-preserving computation under the basic data system [J]. Information and Communications Technology and Policy, 2023, 49(4): 48-58.
[3]	ZHANG Zhaolong, XIE Jiang, BAO Hongyu. Thoughts on data security compliance governance in telecommunication field [J]. Information and Communications Technology and Policy, 2023, 49(2): 14-19.
[4]	LI Yufeng, LIU Qi, WEI Liang. Considerations on data security of Internet of Vehicles [J]. Information and Communications Technology and Policy, 2023, 49(2): 2-8.
[5]	HU Guohua, WANG Zhendong, LIU Shaoyu, LI Qiang. Government data security compliance analysis and innovation practice [J]. Information and Communications Technology and Policy, 2023, 49(2): 20-29.
[6]	JU Xin, CAO Jing, CHEN Fozhong, LIU Wenmao, HU Zhonghua. Application and security research of privacy computing in health industry [J]. Information and Communications Technology and Policy, 2023, 49(2): 43-48.
[7]	FENG Shiduo, GAO Jingjie, LI Shenzhi, YAO Nanwei. Research on the evolution trend of ICT supply chain security system [J]. Information and Communications Technology and Policy, 2023, 49(2): 49-53.
[8]	PIAO Hongguo, LIU Minghui. Research on the target framework and implementation scheme of data security compliance system construction [J]. Information and Communications Technology and Policy, 2023, 49(2): 58-64.
[9]	LIANG Qing. Middle platform of data security builds the lifeline of enterprise data [J]. Information and Communications Technology and Policy, 2023, 49(2): 92-96.
[10]	ZHANG Bin, WEN Nuan, QIU Qin, ZHOU Ying, LI Wenqi. Research and practice of data security management in information and communication enterprises [J]. Information and Communications Technology and Policy, 2022, 48(8): 19-23.
[11]	LIU Xin, CAO Jing, SHAO Zhijie, ZHOU Yuefeng. Anti-ransomware research based on data storage technologies [J]. Information and Communications Technology and Policy, 2022, 48(8): 36-42.
[12]	WANG Wei, CAO Jing, CHENG Geng, LI Xueying. Research on reducing the impact of automated decision on personal information security [J]. Information and Communications Technology and Policy, 2022, 48(8): 52-58.
[13]	WEI Kai, YAN Shu, LYU Ailin. An overview on the market-based allocation of data factor [J]. Information and Communications Technology and Policy, 2022, 48(8): 59-64.
[14]	ZHOU Bohui, YU Le, MA Yusheng, PAN Jiali. Patent situation analysis of data security technology [J]. Information and Communications Technology and Policy, 2022, 48(7): 87-91.
[15]	GUO Zhen, LI Shuaizheng. Thinking on the path of accelerating the development of digital economy based on artificial intelligence [J]. Information and Communications Technology and Policy, 2022, 48(6): 69-74.