摘要
随着人工智能和材料科学数据驱动的材料设计热潮的兴起,材料科学数据成为生产要素、国家战略资源和国际竞争的焦点。然而,随着材料数据共享的增加,数据安全问题变得不可忽视。数据泄露、滥用、篡改等问题威胁着企业竞争力。本文综述了目前主流的数据安全保护技术,包括访问控制、加密技术,构成了传统的数据安全防护模型,实现数据传输、存储时的安全。区块链技术可以实现数据传输、存储时的机密性、完整性、可用性,但是这些机制仍无法解决数据使用时的隐私问题,无法保护使用中的数据机密性、完整性等问题。利用机密计算技术的优势,在硬件可信执行环境中执行计算,最小化计算环境的可信基,提供全方位的数据保护,践行“数据可用不可见”理念,实现对使用中的数据保护,进而构建端到端的全生命周期数据安全。本文结合区块链和机密计算技术的优势,提出基于区块链和机密计算的材料数据可信基础设施方案,以实现数据的全生命周期安全,为材料数据的安全应用提供有力支持。
With the rise of data-driven material design driven by artificial intelligence and materials science,material science data has become a focal point of production factors,national strategic resources,and international competition.However,as material data sharing increases,data security issues become increasingly important.Issues such as data leakage,misuse,and tampering threaten the competitiveness of enterprises.We first review mainstream data security protection technologies,including access control and encryption technologies,which constitute the traditional data security protection model,ensuring security during data transmission and storage.Next,the development of blockchain technology is introduced.Blockchain technology can achieve confidentiality,integrity,and availability during data transmission and storage,but these mechanisms still cannot address privacy issues during data usage,nor can they protect the confidentiality and integrity of data during usage.Then,the advantages of confidential computing technology are analyzed.By executing calculations in a hardware-based trusted execution environment,confidential computing technology minimizes the trusted computing base,providing comprehensive data protection and adhering to the concept of"data usability without visibility"to protect data during usage,thereby constructing end-to-end lifecycle data security.Finally,we combine the advantages of blockchain and confidential computing technology to propose a trustworthy infrastructure solution for material data based on blockchain and confidential computing,to achieve security throughout the data lifecycle and provide strong support for the secure application of material data.
作者
龚海燕
麻付强
张达威
李晓刚
GONG HaiYan;MA FuQiang;ZHANG DaWei;LI XiaoGang(National Materials Corrosion and Protection Data Center,University of Science and Technology Beijing,Beijing 100083,China;Shunde Innovation School,University of Science and Technology Beijing,Foshan 528399,Guangdong,China;Inspur(Beijing)Electronic Information Industry Co.,Ltd,Beijing 100085,China;Inspur Group Co.Ltd.,Jinan 250101,China)
出处
《农业大数据学报》
2024年第2期241-252,共12页
Journal of Agricultural Big Data
基金
国家重点研发项目(2023YFB3812901)
国家资助博士后研究人员计划(资助编号:GZC20230239)
中国博士后科学基金(资助编号:2023M740219)。
关键词
机密计算
区块链
材料数据
数据安全
数据共享
confidential calculations
blockchain
material data
data security
data sharing