{"title":"RF Fingerprint Identification of Commercial UAV in Outdoor Environment","authors":"Ruifei Wang, Zeguang Li, Jie Tang, H. Wen","doi":"10.1109/CCPQT56151.2022.00070","DOIUrl":null,"url":null,"abstract":"In recent years, commercial UAVs (unmanned aerial vehicles) have been widely used in various scenarios, and at the same time, they are also facing serious security threats. The traditional cryptography-based authentication mechanism can hardly meet the needs of new scenarios and applications, so RF fingerprint recognition technology with low complexity and high security has gradually become a research hotspot. There is a large literature on this aspect of research and experimentation. However, most of the data used in experiments are from laboratories or open outdoor environments with LoS (Line of Sight) signals. In practical application scenarios, commercial UAVs may work in some outdoor environments with complex interference factors. Therefore, this work proposes the verification of the RF fingerprint recognition capability of commercial UAVs in complex outdoor scenarios.","PeriodicalId":235893,"journal":{"name":"2022 International Conference on Computing, Communication, Perception and Quantum Technology (CCPQT)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Computing, Communication, Perception and Quantum Technology (CCPQT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCPQT56151.2022.00070","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In recent years, commercial UAVs (unmanned aerial vehicles) have been widely used in various scenarios, and at the same time, they are also facing serious security threats. The traditional cryptography-based authentication mechanism can hardly meet the needs of new scenarios and applications, so RF fingerprint recognition technology with low complexity and high security has gradually become a research hotspot. There is a large literature on this aspect of research and experimentation. However, most of the data used in experiments are from laboratories or open outdoor environments with LoS (Line of Sight) signals. In practical application scenarios, commercial UAVs may work in some outdoor environments with complex interference factors. Therefore, this work proposes the verification of the RF fingerprint recognition capability of commercial UAVs in complex outdoor scenarios.