A RF Fingerprint Based EIoT Device Identification Method

doi:10.11930/j.issn.1004-9649.202005053

Abstract

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

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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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202005053

https://www.electricpower.com.cn/EN/Y2021/V54/I3/80

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