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数据驱动的区块链框架下政府部门间信息共享

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  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
政府部门间的信息共享对提升政府部门的服务和效率具有重要作用。目前尚未有有效且安全的方法实现数据驱动的信息共享以满足政府部门动态的信息共享需求。针对政府部门间信息共享，本文提出了一种利用区块链和数据挖掘技术实现的数据驱动的框架。首先，以区块链为核心设计了整个框架，以实现对政府信息泄露和滥用的监控和预防，保障信息安全;然后，设计了相应的4层次结构，用以实现提出的框架;其次，采用了经典的数据挖掘算法PageRank和Apriori动态设计信息共享的智能合约，以实现基于政府部门对公共管理和公共服务的实际需求灵活调整信息共享策略的目的;最后，给出了解释此框架如何运作的一个案例研究。
Inter-agency government information sharing under data-driven blockchain framework
The inter-agency government information sharing(IAGIS)plays an important role in improving service and efficiency of government agencies.Currently,there is still no effective and secure way for data-driven IAGIS to fulfill dynamic demands of information sharing between government agencies.Motivated by blockchain and data mining,a data-driven framework is proposed for IAGIS in this paper.Firstly,the blockchain is used as the core to design the whole framework for monitoring and preventing leakage and abuse of government information,in order to guarantee information security.Secondly,a four-layer architecture is designed for implementing the proposed framework.Thirdly,the classical data mining algorithms PageRank and Apriori are applied to dynamically design smart contracts for information sharing,for the purposed of flexibly adjusting the information sharing strategies according to the practical demands of government agencies for public management and public service.Finally,a case study is presented to illustrate the operation of the proposed framework.

government data processingblockchainPageRankapriori

肖炯恩、洪明、丁丽萍

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广东财经大学国际商学院,广东广州 510320

广州软件应用技术研究院电子取证实验室,广东广州 511400

华南理工大学电子商务系,广东广州 510641

中国科学院软件研究所,北京 100190

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政府数据处理 区块链 PageRank apriori

Project of Guangdong Science and Technology DepartmentPost-Doctoral Research ProjectMinistry of Education Social Science FundFund project of Department of Science and Technology of Guangdong ProvinceGuangdong Philosophy and Social Science

2020B010166005Z00015822YJ630167GDK TP2021032500GD22YYJ15

2024

10.7641/CTA.2023.220718

控制理论与应用
华南理工大学 中国科学院数学与系统科学研究院

控制理论与应用

CSTPCD北大核心
影响因子：1.076
ISSN：1000-8152
年,卷(期)：2024.41(8)