一种基于射频指纹的电力物联网设备身份识别方法

doi:10.11930/j.issn.1004-9649.202005053

中国电力 ›› 2021, Vol. 54 ›› Issue (3): 80-88.DOI: 10.11930/j.issn.1004-9649.202005053

• 5G等新一代信息技术在能源互联网中的应用研究 • 上一篇下一篇

一种基于射频指纹的电力物联网设备身份识别方法

刘铭¹, 刘念¹, 韩晓艺¹, 彭林宁², 付华², 陈一悰³

1. 北京交通大学计算机与信息技术学院(交通数据分析与挖掘北京市重点实验室)北京 100044;
2. 东南大学网络空间安全学院，江苏南京 210096;
3. 国网陕西省电力公司电力科学研究院，陕西西安 710054

收稿日期:2020-05-08 修回日期:2020-07-18 出版日期:2021-03-05 发布日期:2021-03-17
作者简介:刘铭(1982-)，男，通信作者，博士，副教授，从事5G、物联网、无线网络物理层安全研究，E-mail：mingliu@bjtu.edu.cn
基金资助:
国家自然科学基金资助项目(基于设备指纹的无线物联网设备身份识别研究，61971029)；江苏省重点研发计划资助项目(BE2019109)

A RF Fingerprint Based EIoT Device Identification Method

LIU Ming¹, LIU Nian¹, HAN Xiaoyi¹, PENG Linning², FU Hua², CHEN Yicong³

1. School of Computer and Information Technology (Beijing Key Lab. of Transportation Data Analysis and Mining), Beijing Jiaotong University, Beijing 100044, China;
2. School of Cyber Science and Engineering, Southeast University, Nanjing 210096, China;
3. State Grid Shanxi Electric Power Research Institute, Xi'an 710054, China

Received:2020-05-08 Revised:2020-07-18 Online:2021-03-05 Published:2021-03-17
Supported by:
This work is supported by the National Natural Science Foundation of China (Research on Identification of Wireless IoT Device Based on Device Fingerprint, No.61971029) and Jiangsu Key R & D Plan (No.BE2019109)

摘要/Abstract

摘要： 由于通信媒介的开放性，电力物联网设备的无线通信过程面临着信息安全风险。提出使用无线设备固有的射频指纹作为物联网设备身份识别的依据，并利用深度学习技术实现双向设备身份识别，以增强无线接入阶段的安全性。该方法采用边缘计算的思路，利用通信信道双向的互易性，将物联网终端设备需要完成的基站身份学习任务转移到基站处完成，降低了对于物联网设备算力、存储、能耗等方面的需求，适用于物联网应用场景。实验结果表明，该方法能够达到良好的设备身份识别性能。

关键词: 电力物联网, 射频指纹, 无线接入安全, 信道互易, 设备身份识别

Abstract: Due to the openness nature of the communication medium, the wireless communication of Electric Internet of Things (EIoT) devices faces severe security risks. It is proposed in this paper to adopt the natural radio frequency fingerprint (RFF) of wireless devices as the basis for IoT device identification, and use the deep learning techniques to achieve bi-directional device identification, so as to enhance the communication security at the wireless access stage. Based on the technical thinking of edge computing and the bi-directional channel reciprocity of communication, the proposed method offloads the learning task of IoT terminals to the base station so that the proposed RFF-based device identification method can meet the demands of computation, storage, and power consumption of the IoT scenarios. Experimental results show that the proposed method can achieve good device identification performance.

Key words: Electric Internet of Things, radio frequency fingerprint, radio access security, channel reciprocity, device identification

刘铭, 刘念, 韩晓艺, 彭林宁, 付华, 陈一悰. 一种基于射频指纹的电力物联网设备身份识别方法[J]. 中国电力, 2021, 54(3): 80-88.

LIU Ming, LIU Nian, HAN Xiaoyi, PENG Linning, FU Hua, CHEN Yicong. A RF Fingerprint Based EIoT Device Identification Method[J]. Electric Power, 2021, 54(3): 80-88.

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一种基于射频指纹的电力物联网设备身份识别方法

A RF Fingerprint Based EIoT Device Identification Method

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一种基于射频指纹的电力物联网设备身份识别方法

A RF Fingerprint Based EIoT Device Identification Method

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