广州大学网络空间安全学院,广东广州 510555
[ "张瑶瑶 女,1998年10月出生于河南省郑州市.现为广州大学网络空间安全学院博士研究生.主要研究方向为区块链与数据交易.E-mail: yaoaoz@e.gzhu.edu.cn" ]
[ "周圆 女,1994年3月出生于河南省信阳市.现为广州大学网络空间安全学院博士研究生.主要研究方向为网络威胁情报共享机制.E-mail: wendribs@e.gzhu.edu.cn" ]
[ "杨青林 男,1989年4月出生于河南省项城市.现为广州大学网络空间安全学院特聘讲师.主要研究方向为区块链、联邦学习.在国外相关领域主流期刊和会议上发表论文40余篇,主持广州市高校科研面上项目1项,横向课题1项,主持国家重点研发计划青年项目子任务.E-mail: yangqinglin@gzhu.edu.cn" ]
[ "颛孙晨露 女,1990年9月出生于安徽省宿州市.现为广州大学网络空间安全学院特聘讲师.主要研究方向为主动防御、欺骗防御及信誉系统等.E-mail: chenluzhuansun@gzhu.edu.cn" ]
[ "陈凯 男,1997年9月出生于江苏省南通市.现为广州大学网络空间安全学院在读硕士研究生.主要研究方向为区块链安全、联邦学习.E-mail: kaichen@e.gzhu.edu.cn" ]
[ "李意 男,2000年2月出生于广东省广州市.现为广州大学网络空间安全学院在读硕士研究生.主要研究方向为IPv6空间探测、IPv6应用、区块链应用.E-mail: yuegeyu@e.gzhu.edu.cn" ]
[ "刘园 女,1986年10月出生于吉林省长春市.现为广州大学网络空间安全学院教授、博士生导师.主要研究方向为网络安全、数据安全、区块链安全.国家自然科学基金获得者、国家重点研发计划项目项目负责人.发表学术论文100余篇,专著1部.E-mail: yuanliu@gzhu.edu.cn" ]
[ "田志宏 男,1978年9月出生于黑龙江省哈尔滨市.现为广州大学副校长,网络空间安全学院教授、博士生导师,国家级人才项目特聘教授.主要研究方向为网络攻防对抗,网络靶场、主动实时防护等.获得省部级奖励4次,发表论文200余篇,专著3部.E-mail: tianzhihong@gzhu.edu.cn" ]
收稿:2025-04-30,
录用:2025-10-24,
纸质出版:2025-10-25
移动端阅览
张瑶瑶, 周圆, 杨青林, 等. 区块链赋能数据存储安全服务研究进展[J]. 电子学报, 2025, 53(10): 3794-3816.
ZHANG Yao-yao, ZHOU Yuan, YANG Qing-lin, et al. Research Progress on Blockchain-Empowered Data Storage Security Service[J]. Acta Electronica Sinica, 2025, 53(10): 3794-3816.
张瑶瑶, 周圆, 杨青林, 等. 区块链赋能数据存储安全服务研究进展[J]. 电子学报, 2025, 53(10): 3794-3816. DOI:10.12263/DZXB.20250347
ZHANG Yao-yao, ZHOU Yuan, YANG Qing-lin, et al. Research Progress on Blockchain-Empowered Data Storage Security Service[J]. Acta Electronica Sinica, 2025, 53(10): 3794-3816. DOI:10.12263/DZXB.20250347
随着数字经济的高速发展,数据存储已成为数据要素全生命周期管理的核心环节,在完整性、隐私性、可用性等安全属性上面临多重挑战.区块链依托分布式账本数据结构与密码学共识机制,构建起覆盖数据全生命周期可信存储的基座,为破解安全挑战提供创新技术路径.然而现有区块链技术在可扩展性、效率优化和安全加固等方面仍存在局限,亟需系统梳理区块链赋能数据安全的技术路径与能力边界.本文围绕数据安全服务“数据上链、服务访问、授权管理、生态运营”等关键业务,系统性调研区块链赋能数据安全研究进展,并面向数据安全利用和价值流通等数据产业安全发展指明技术发展趋势.具体地,本文首先从数据上链存储环节出发,分析影响数据完整性的共识机制、可编辑区块链以及完整性审计技术现状;其次在服务访问环节,分析拒绝服务(Denial-of-Service,DoS)攻击和低效率功能两类威胁的攻击原理,并对比当前存储可用性方案的优缺点;面对授权管理环节,从身份管理和密文存储两方面讨论数据跨域和非法访问问题及分析现有解决方案;面对数据存储安全服务生态运营需求,探索可扩展性的共识协议和分片机制两类技术,分析其成本、效率与适配性等方面瓶颈;最后,讨论区块链在数据安全领域赋能大语言模型(Large Language Model,LLM)安全的能力,并展望区块链在抗量子密码算法的能效优化机制、基于联邦学习的区块链弹性扩展架构,以及可信数据要素驱动的大语言模型等研究方向的发展趋势.
With the rapid growth of the digital economy
data storage has become a critical component in the whole management cycle
but it encounters several critical security challenges
such as content integrity
privacy preservation
and sustainable availability. Benefiting from the distributed ledger structure and cryptographic consensus mechanisms
blockchain technology provides a trustworthy solution for addressing these security challenges. Given the fact that the current blockchain systems remain constrained by scalability
efficiency
and security limitations
it is essential to conduct a systematic review of their data storage service capacities and analyze their security boundaries. This paper provides a comprehensive survey of research progress in blockchain-enabled data security by investigating its key procedures
including data on-chain storage
service access
authorization management
and ecological operation to identify emerging technical trends towards secure data utilization and value exchange. Specifically
this paper begins by examining the data on-chain storage phase
analyzing the current state of consensus mechanisms
editable blockchains
and integrity auditing technologies that impact data integrity. Next
in the service access phase
it analyzes the attack principles of two types of threats - DoS (Denial-of-Service) attacks and inefficient functionality - and compares the strengths and weaknesses of existing storage availability solutions. Regarding the authorization management phase
it discusses cross-domain data and unauthorized access issues from the perspectives of identity management and ciphertext storage
while analyzing existing solutions. In response to the ecological operation needs of data storage security service
it explores two types of technologies — scalable consensus protocols and sharding mechanisms — analyzing their bottlenecks in terms of cost
efficiency
and adaptability. Finally
it discusses blockchain’s capability to empower LLM (Large Language Models) in the field of data security and looks ahead to research trends
including energy-efficient optimization mechanisms for post-quantum cryptographic algorithms
blockchain elastic scaling architectures based on federated learning
and trusted data element-driven LLMs.
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