基于区块链的挤压铸造工艺数据库共享安全访问控制系统

IF 2.4 3区 材料科学 Q3 ENGINEERING, MANUFACTURING
Jianxin Deng, Gang Liu, Xiangming Zeng
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引用次数: 0

摘要

目前,材料数据库建设是一个热门话题。我们建议采用协作共享模式,加快挤压铸造工艺数据库的建设。为实现数据库的共建共享,确保数据的可靠性、数据库运行的安全性和数据的按需访问控制,我们建立了基于区块链技术的挤压铸造工艺数据库安全访问控制系统。该系统将数据库数据保存在本地服务器上,通过智能合约实现用户自动访问控制,将用户操作记录存储在区块链上,确保数据可修改,用户操作记录不可篡改。由于传统交易过程中数据作为源数据传输,安全性不足,我们采用非对称加密算法对源数据进行加密,传输密文,提高数据共享安全性。该系统已经开发并实现,安全验证实验证明了设计的可行性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Blockchain-Based Security Access Control System for Sharing Squeeze Casting Process Database

Blockchain-Based Security Access Control System for Sharing Squeeze Casting Process Database

Presently, material databases construction is a trending topic. We propose to adopt a collaborative and shared model to accelerate building a squeeze casting process database. To achieve co-construction and sharing of the databases, ensure the reliability of data, database operation security, and on-demand access control of data, a secure access control system has been established for squeeze casting process databases based on blockchain technology. The system saves the database data on a local server, implements automatic access control for users through smart contracts, stores user operation records on the blockchain, and ensures that the data is modifiable while the user operation records cannot be tampered with. Because of the inadequate security of traditional transaction processes where data is transmitted as source data, we use asymmetric encryption algorithm to encrypt the source data and transmit ciphertext to improve data sharing security. The system has been developed and implemented, and the security verification experiment has demonstrated the feasibility and effectiveness of the design.

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来源期刊
Integrating Materials and Manufacturing Innovation
Integrating Materials and Manufacturing Innovation Engineering-Industrial and Manufacturing Engineering
CiteScore
5.30
自引率
9.10%
发文量
42
审稿时长
39 days
期刊介绍: The journal will publish: Research that supports building a model-based definition of materials and processes that is compatible with model-based engineering design processes and multidisciplinary design optimization; Descriptions of novel experimental or computational tools or data analysis techniques, and their application, that are to be used for ICME; Best practices in verification and validation of computational tools, sensitivity analysis, uncertainty quantification, and data management, as well as standards and protocols for software integration and exchange of data; In-depth descriptions of data, databases, and database tools; Detailed case studies on efforts, and their impact, that integrate experiment and computation to solve an enduring engineering problem in materials and manufacturing.
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