Lightweight Data Security Protection Method for AMI in Power Internet of Things

Author:

Jiang Wenqian12,Yang Zhou1ORCID,Zhou Zhenglei1,Chen Jueyu1

Affiliation:

1. Measurement Center, Guangxi Power Grid Co., Ltd., Nanning 530010, China

2. School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China

Abstract

Aiming at the security problems caused by the access of a large number of new advanced metering system (AMI) equipment and the rapid growth of new business data interaction volume and interaction frequency, a lightweight data security protection method for power Internet of things (IoT) is proposed. Firstly, based on the “cloud-edge-end” AMI system architecture, a multilevel anonymous authentication method is proposed to reduce the complexity of low-end equipment access without reauthentication when smart meters and other devices access the system. Then, when fully homomorphic encryption is used for data encryption transmission, the lightweight packet recombination protocol is introduced, the lightweight hash function is used to reduce the calculation cost, and the sliding address window mechanism is used to reduce the packet loss rate. Finally, improved secure multiparty computing (SMPC) is used to achieve frequency hopping data aggregation, using shared key to calculate local shared value for key update, reducing data interaction between massive devices and AMI cloud security server, and improving broadband utilization in data aggregation process. The experiment results indicate that the proposed method obtained better utilization in bandwidth and shorter average data collection completion time. Besides, the proposed method can ensure the information security in the interaction process.

Funder

Guangxi Power Grid Co., Ltd., Science and Technology Project

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

Reference23 articles.

1. Power data privacy protection based on empirical mode decomposition and homomorphic encryption;Y. C. Li;Power System Technology,2019

2. Distilling at the Edge: A Local Differential Privacy Obfuscation Framework for IoT Data Analytics

3. Survey on synchrophasor data quality and cybersecurity challenges, and evaluation of their interdependencies

4. Smart grid blind online false data injection attack based on nuclear principal component analysis;Y. C. Li;Power System Technology,2018

5. Non-linear state recovery in power system under bad data and cyber attacks

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3