基于噪声干扰的智能电网终端电磁泄漏防御方法

doi:10.3969/j.issn.1008-0198.2025.04.019

湖南电力 ›› 2025, Vol. 45 ›› Issue (4): 133-142.doi: 10.3969/j.issn.1008-0198.2025.04.019

• 电力人工智能与数字化 • 上一篇下一篇

基于噪声干扰的智能电网终端电磁泄漏防御方法

龙彦伯^1,2, 乔宏^1,2, 王剀艺³, 肖剑^1,2, 刘帅^1,2

1.国网湖南省电力有限公司电力科学研究院,湖南长沙 410208;
2.湖南省电力多模态感知与边缘智能工程技术研究中心,湖南长沙 410208;
3.湖南大学信息科学与工程学院,湖南长沙 410007

收稿日期:2025-03-31 修回日期:2025-06-13 出版日期:2025-08-25 发布日期:2025-09-05
通信作者: 龙彦伯(1996),男,主要从事网络安全与人工智能研究工作。
基金资助:
国网湖南省电力有限公司科技项目（5216A522001V）

Electromagnetic Leakage Defense Method for Smart Grid Terminals Based on Noise Interference

LONG Yanbo^1,2, QIAO Hong^1,2, WANG Kaiyi³, XIAO Jian^1,2, LIU Shuai^1,2

1. State Grid Hunan Electric Power Company Limited Research Institute, Changsha 410208, China;
2. Hunan Province Engineering Technology Research Center of Electric Power Multimodal Perception and Edge Intelligence, Changsha 410208, China;
3. College of Computer Science and Electronic Engineering, Hunan University, Changsha 410007, China

Received:2025-03-31 Revised:2025-06-13 Online:2025-08-25 Published:2025-09-05

摘要/Abstract

摘要： 针对智能电网终端可能存在的电磁泄漏漏洞,系统分析智能电网终端电磁泄漏的机理与传播路径,指出人体作为导体形成共模耦合是电磁信号泄漏的主要途径。针对传统防御方法在智能电网终端场景下的局限性,提出基于噪声干扰的防御方法,设计一种通过静电手环向人体注入随机频率(100 Hz以下)、随机幅度(1~3 V)干扰信号的装置。实验结果表明,所提出的防御方法能够有效降低电磁侧信号的泄漏,尤其在配电自动化应用中可提升智能电网终端敏感操作过程的安全性。

关键词: 智能电网终端, 电磁泄漏防御, 噪声干扰, 机器学习

Abstract: For potential electromagnetic leakage vulnerabilities in smart grid terminals, the mechanism and propagation path of electromagnetic leakage in smart grid terminal are systematically analyzed, revealing that the human body as a conductor forms common-mode coupling, which is the main channel for electromagnetic signal leakage. In view of the limitations of traditional defense methods in smart grid terminal scenarios, a defense method based on noise interference is proposed. A device is designed to inject random-frequency (below 100 Hz) and random-amplitude (1~3 V) interference signals into the human body through an electrostatic wristband. Experimental results show that the proposed defense method can effectively reduce information leakage via electromagnetic side channels, enhance the security of sensitive operation process in smart grid terminals (especially in distribution automation applications) and offer a new technical idea for the construction of information security protection systems in new power systems.

Key words: smart grid terminal, electromagnetic leakage defense, noise interference, machine learning

中图分类号:

TM727

龙彦伯, 乔宏, 王剀艺, 肖剑, 刘帅. 基于噪声干扰的智能电网终端电磁泄漏防御方法[J]. 湖南电力, 2025, 45(4): 133-142.

LONG Yanbo, QIAO Hong, WANG Kaiyi, XIAO Jian, LIU Shuai. Electromagnetic Leakage Defense Method for Smart Grid Terminals Based on Noise Interference[J]. Hunan Electric Power, 2025, 45(4): 133-142.

参考文献

[1] 李春玲. 抗侧信道攻击Fixed-base Comb算法设计[J]. 青海师范大学学报:自然科学版,2006(4):41-45,57.
[2] BERGER Y,WOOL A,YEREDOR A.Dictionary attacks using keyboard acoustic emanations[C]//Proceedings of the 13th ACM Conference on Computer and Communications Security. Alexandria Virginia USA.ACM,2006:245-254.
[3] FOO KUNE D, KIM Y.Timing attacks on PIN input devices[C]//Proceedings of the 17th ACM Conference on Computer and Communications Security. Chicago Illinois USA. ACM, 2010: 678-680.
[4] LIU J,WANG Y,KAR G,et al.Snooping keystrokes with mm-level audio ranging on a Single phone[C]//Proceedings of the 21st Annual International Conference on Mobile Computing and Networking. Paris France. ACM,2015:142-154.
[5] LU L,YU J,CHEN Y,et al.Keylistener: inferring keystrokes on qwerty keyboard of touch screen through acoustic signals[C]//IEEE INFOCOM 2019-IEEE Conference on Computer Communications. IEEE,2019:775-783.
[6] SHUMAILOV I,SIMON L,YAN J,et al. Hearing your touch:A new acoustic side channel on smartphones[EB/OL].2019:1903.11137. https://arxiv.org/abs/1903.11137v1.
[7] ZHU T,MA Q,ZHANG S,et al.Context-free attacks using keyboard acoustic emanations[C]//Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security. Scottsdale Arizona USA. ACM,2014:453-464.
[8] BACKES M,CHEN T,DÜRMUTH M,et al. Tempest in a teapot:compromising reflections revisited[C]//2009 30th IEEE Symposium on Security and Privacy. Oakland,CA,USA.IEEE,2009:315-327.
[9] BACKES M,DÜRMUTH M,UNRUH D. Compromising reflections-or-how to read LCD monitors around the corner[C]//2008 IEEE Symposium on Security and Privacy(sp 2008). Oakland,CA,USA. IEEE,2008:158-169.
[10] CHEN Y,LI T,ZHANG R,et al.Eyetell:video-assisted touchscreen keystroke inference from eye movements[C]//2018 IEEE Symposium on Security and Privacy(SP). San Francisco,CA.IEEE,2018:144-160.
[11] RAGURAM R,WHITE A M,GOSWAMI D,et al.ISpy:automatic reconstruction of typed input from compromising reflections[C]//Proceedings of the 18th ACM Conference on Computer and Communications Security. Chicago Illinois USA. ACM,2011:527-536.
[12] WANG Y,CAI W D,GU T,et al.Your eyes reveal your secrets:an eye movement based password inference on smartphone[J]. IEEE Transactions on Mobile Computing,2020,19(11):2714-2730.
[13] WANG Y,CAI W D,GU T,et al.GazeRevealer:inferring password using smartphone front camera[C]//Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems:Computing,Networking and Services. New York NY USA. ACM,2018:254-263.
[14] XU Y,HEINLY J,WHITE A M,et al.Seeing double:reconstructing obscured typed input from repeated compromising reflections[C]//Proceedings of the 2013 ACM SIGSAC Conference on Computer & Communications Security-CCS’13. Berlin,Germany. ACM Press,2013:1063-1074.
[15] ALI K,LIU A X,WANG W,et al.Keystroke recognition using WiFi signals[C]//Proceedings of the 21st Annual International Conference on Mobile Computing and Networking. Paris France. ACM,2015:90-102.
[16] FANG S,MARKWOOD I,LIU Y,et al.No training hurdles: fast training-agnostic attacks to infer your typing[C]//Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security. Toronto Canada:ACM. 2018:1747-1760.
[17] LI M,MENG Y,LIU J,et al.When CSI meets public WiFi:inferring your mobile phone password via WiFi signals[C]//Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. Vienna Austria. ACM,2016:1068-1079.
[18] LING K,LIU Y,SUN K,et al.SpiderMon:towards using cell towers as illuminating sources for keystroke monitoring[C]//IEEE INFOCOM 2020-IEEE Conference on Computer Communications. IEEE,2020:666-675.
[19] VUAGNOUX M,PASINI S.Compromising electromagnetic emanations of wired and wireless keyboards[J]. Proceedings of the 18th USENIX Security Symposium,2009:1-16.
[20] DU Y L,LU Y H,ZHANG J L.Novel method to detect and recover the keystrokes of ps/2 keyboard[J]. Progress in Electromagnetics Research C,2013,41:151-161.
[21] WANG L,YU B.Analysis and measurement on the electromagnetic compromising emanations of computer keyboards[C]//2011 Seventh International Conference on Computational Intelligence and Security. IEEE,2011:640-643.
[22] 区健昌. 电子设备的电磁兼容性设计[M]. 北京:电子工业出版社,2003.
[23] JIN W Q,MURALI S,ZHU H D,et al.Periscope:A keystroke inference attack using human coupled electromagnetic emanations[C]//Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security. Virtual Event Republic of Korea. ACM,2021:700-714.
[24] LEHTINEN R,RUSSELL D,GANGEMI SR G T. Computer security basics[M]. Sebastopol,California:O’Reilly Media Inc.,2006.

基于噪声干扰的智能电网终端电磁泄漏防御方法

Electromagnetic Leakage Defense Method for Smart Grid Terminals Based on Noise Interference

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 3

编辑推荐

Metrics

本文评价

[1]	周驰东, 于婧, 郁亚娟, 常泽宇, 陈来, 苏岳锋. 基于单一和多元特征的锂离子电池健康状态预测平台设计与实现[J]. 湖南电力, 2025, 45(1): 14-20.
[2]	余忠泽, 刘震卿, 马驰. 基于尾流效应与机器学习的风功率预测研究[J]. 湖南电力, 2023, 43(3): 53-59.
[3]	周慧, 王瑶, 罗仁强, 党俊榜, 肖振馨, 赵航. 基于大数据挖掘与规则引擎的智慧辅助监盘系统研究[J]. 湖南电力, 2023, 43(3): 77-81.