网络与信息安全学报2025，Vol.11Issue(2)：152-160,9.DOI:10.11959/j.issn.2096-109x.2025024
基于句法模式识别的射频指纹识别方法
Radio frequency fingerprint identification method based on syntactic recognition
摘要
Abstract
To address the difficulty in feature extraction due to channel characteristics and noise influence,a method based on syntactic pattern recognition was proposed.Using the 802.11 Wi-Fi signal as the object,a hierar-chical syntactic model was constructed based on the folding features of the radio frequency fingerprint(RFF)ampli-tude spectrum to achieve feature compression.The local form of the amplitude spectrum was summarized into four elements:peak,valley,upper flat shoulder,and lower flat shoulder.Three layers of syntactic mapping rules were es-tablished.The first layer extracted single line segment features(straight,rise,fall),the second layer combined adja-cent segments to generate double line segment features(e.g.,peak and valley),and the third layer integrated charac-teristic position and level value.Additionally,a subgraph fusion algorithm was proposed.Through embedding,pruning,and topology rearrangement,various syntactic models of similar equipment were integrated.Ultimately,the RFF features were compressed by 60%to 66%(from 50 dimensions to 30-33 dimensions).Experiments using 10 ESP32-WROOM 32U modules demonstrate that with a signal-to-noise ratio of 25 dB,the accuracy of the K-nearest neighbor and naive Bayes classifiers is improved by 4.3%and 5.0%,respectively.Both the intra-class error rate and inter-class error rate of open set identification are below 10.72%.This method can reduce data dimension-ality while maintaining high discriminability,offering a novel approach for RFF identification.关键词
射频指纹/Wi-Fi信号/句法模式识别/物理层安全Key words
radio frequency fingerprint/Wi-Fi signal/syntax recognition/physical layer safety分类
信息技术与安全科学引用本文复制引用
陈彦君,胡爱群..基于句法模式识别的射频指纹识别方法[J].网络与信息安全学报,2025,11(2):152-160,9.基金项目
国家自然科学基金(62171120) The National Natural Science Foundation of china(62171120) （62171120）
