基于加密算法的电力物联网电能质量数据安全传输方法

IF 0.5 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Xin Liu, Yingxian Chang, Honglei Yao, Bing Su
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引用次数: 0

摘要

5G作为物联网时代的一种新型移动通信技术,具有高速、低延迟、大连接等特点。它是在物联网时代实现人机和物联网的网络基础设施。电能质量数据是指电网向用户输送电力的效率,并表示一台机器使用其接收的电力的情况。额定电压和频率下的波形是电能质量研究和改进的目标。电力物联网(IoT)是一个智能服务平台,充分利用尖端技术实现用户-机器交互、数据驱动决策、实时分析和自适应软件设计。将明文转换为密文的过程称为加密算法。密文可能看起来完全是随机的,但可以使用创建加密密钥的确切机制进行解密。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Secure Transmission Method of Power Quality Data in Power Internet of Things Based on the Encryption Algorithm
As a new mobile communication technology in the era of the internet of things, 5G is characterized by high speed, low delay, and large connection. It is a network infrastructure to realize human-computer and internet of things in the era of the internet of things. Power quality data is the efficiency with which a power grid delivers electricity to users and expresses how well a piece of machinery uses the electricity it receives. The waveform at the nominal voltage and frequency is the goal of power quality research and improvement. The power internet of things (IoT) is an intelligent service platform that fully uses cutting-edge tech to enable user-machine interaction, data-driven decision-making, real-time analytics, and adaptive software design. The process by which plaintext is converted into cipher text is called an encryption algorithm. The cipher text may seem completely random, but it can be decrypted using the exact mechanism that created the encryption key.
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来源期刊
International Journal of Data Warehousing and Mining
International Journal of Data Warehousing and Mining COMPUTER SCIENCE, SOFTWARE ENGINEERING-
CiteScore
2.40
自引率
0.00%
发文量
20
审稿时长
>12 weeks
期刊介绍: The International Journal of Data Warehousing and Mining (IJDWM) disseminates the latest international research findings in the areas of data management and analyzation. IJDWM provides a forum for state-of-the-art developments and research, as well as current innovative activities focusing on the integration between the fields of data warehousing and data mining. Emphasizing applicability to real world problems, this journal meets the needs of both academic researchers and practicing IT professionals.The journal is devoted to the publications of high quality papers on theoretical developments and practical applications in data warehousing and data mining. Original research papers, state-of-the-art reviews, and technical notes are invited for publications. The journal accepts paper submission of any work relevant to data warehousing and data mining. Special attention will be given to papers focusing on mining of data from data warehouses; integration of databases, data warehousing, and data mining; and holistic approaches to mining and archiving
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