StableFP:NN-Based Hardware Fingerprint Extractor for LoRa Device Identification

作     者：Qianwu Chen Mingqi Xie Meng Jin Xiaohua Tian 

作者机构：School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China 

出 版 物：《Journal of Communications and Information Networks》 (通信与信息网络学报（英文）)

年 卷 期：2024年第9卷第3期

页      面：244-250页

核心收录：

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

基　　金：supported by the National Natural Science Foundation of China under Grant 62272293 

主　　题：hardware fingerprint Internet-of-things(IoT) LoRa 

摘      要：Hardware fingerprint is a new dimension of security mechanisms in low power wide area networks(LPWANs).It is hard to emulate for attackers and does not increase the computing and energy burden of *** range(LoRa)is a long-range communication technology designed for battery-powered *** practice,LoRa is vulnerable to malicious attacks such as replace ***,the hardware fingerprint is an excellent supplementary mechanism of LoRa ***,the variable wireless environment contaminates the extracted *** long wireless channel adds a large amount of the environment dependent information to the hardware features extracted from LoRa *** this paper,we propose StableFP which is a neural network(NN)based device identifier for long range wide area network(LoRaWAN).StableFP extracts stable and representative hardware features from channel frequency response(CFR)as the fingerprint,and it eliminates the environment dependent information caused by wireless *** implement StableFP on a software defined radio(SDR)testbed which consists of 4 commercial LoRa *** result demonstrates that StableFP achieves over 90%identification accuracy in unseen environments under an over 5 dB signal to noise ratio(SNR).