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机构地区:[1]国网上海市电力公司数字化工作部,上海 [2]上海欣能信息科技发展有限公司安全生产部,上海
出 处:《计算机科学与应用》2023年第11期2062-2071,共10页Computer Science and Application
摘 要:分布式计算虽然能弥补传统集中式计算网络拥堵、计算能力低的缺点,但对边缘设备隐私安全和可信感知存在不足。随着数字新技术的快速发展,利用新一代信息技术满足边云现场环境下的边云数据协同需求日益增长。本论文首先通过研究边缘计算和云计算的发展趋势,识别边云协同关键技术,然后分析边云数据协同面临的数据传输安全、数据通信安全、数据存储安全等问题,得出边云数据协同安全风险方法措施,最后结合边云现场环境下的工业信息物理系统数据协同安全需求,提出了一种基于边云协同的动态数据安全存储策略,该策略以“事前准备–事中防御–事后响应”为指导思想,既能够充分利用云计算和边缘计算的技术优势,又可以满足数据协同的安全性和实时性要求。Although distributed computing can compensate for the shortcomings of traditional centralized computing network congestion and low computing power, it has shortcomings in privacy security and trustworthiness perception of edge devices. With the rapid development of new digital tech-nologies, the demand for edge cloud data collaboration in edge cloud on-site environments is in-creasingly increasing through the use of next-generation information technology. This paper first identifies the key technologies of edge cloud collaboration by studying the development trend of edge computing and cloud computing, then analyzes the data transmission security, data commu-nication security, data storage security and other issues faced by edge cloud data collaboration, and obtains the risk methods and measures of edge cloud data collaboration security. Finally, combined with the data collaboration security requirements of industrial information physics systems under the edge cloud on-site environment, a dynamic data security storage strategy based on edge cloud collaboration is proposed. The strategy takes “preparation in advance-defense in the event-response after the event” as the guiding ideology, which can not only make full use of the technical advantages of cloud computing and edge computing, but also meet the security and re-al-time requirements of data collaboration.
分 类 号:TP3[自动化与计算机技术—计算机科学与技术]
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