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Received:April 22, 2025 Revised:June 05, 2025
Received:April 22, 2025 Revised:June 05, 2025
中文摘要: 由于文化市场执法环境复杂且电子证据固定困难, 根据文化市场综合执法场景功能需求, 提出一种基于区块链的行政执法全流程管理模型. 针对执法过程中案件文书可能面临更新的问题, 提出一种基于随机委员会综合验证的区块链修订方法, 通过可验证随机函数选择一定数量用户组成投票委员会, 对修订内容进行审核后添加至链尾, 保证区块链的前后一致性. 同时, 为加强敏感信息的隐私保护提出一种链上数据访问控制方法, 通过双重加密和策略配置保证数据跨部门共享的安全性. 经过模型分析和对比实验, 证明所提模型能够满足安全性和可靠性需求, 为执法信息化和智能化提供可信的数据基础.
Abstract:Due to the complex law enforcement environment in the cultural market and the difficulty in fixing electronic evidence, a blockchain-based full-process administrative law enforcement management model is proposed according to the functional needs of comprehensive law enforcement on the cultural market. In response to the possible updates in case documents during law enforcement, a blockchain revision method is proposed based on comprehensive verification of the random committee. Through the verifiable random function, a certain number of users are selected to form a voting committee, review the revision content, and add it to the end of the chain to ensure the consistency of the blockchain. At the same time, an on-chain data access control method is put forward to strengthen the privacy protection of sensitive information, ensuring the security of across-department data sharing through dual encryption and policy configuration. After model analysis and comparison experiments, the proposed model is proven to meet the security and reliability needs, providing a reliable data foundation for the informationalized and intelligent law enforcement.
keywords: blockchain digital forensics full-process management verified random function access control
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基金项目:复杂关键软件环境全国重点实验室课题(SKLSDE-2024ZX-09); 沈元学院卓越研究基金(250123186)
引用文本:
吴非,沈润楠.基于区块链的执法全流程存证模型.计算机系统应用,2025,34(12):119-128
WU Fei,SHEN Run-Nan.Blockchain-based Full-process Evidence Preservation Model for Law Enforcement.COMPUTER SYSTEMS APPLICATIONS,2025,34(12):119-128
吴非,沈润楠.基于区块链的执法全流程存证模型.计算机系统应用,2025,34(12):119-128
WU Fei,SHEN Run-Nan.Blockchain-based Full-process Evidence Preservation Model for Law Enforcement.COMPUTER SYSTEMS APPLICATIONS,2025,34(12):119-128

