{"title":"基于wi - fi的无人机拒绝服务攻击分类","authors":"G. Bertoli, L. A. P. Júnior, O. Saotome","doi":"10.1109/ladc53747.2021.9672561","DOIUrl":null,"url":null,"abstract":"This paper presents an analysis of denial of service (DoS) attacks on Wi-Fi-based Unmanned Aerial Vehicle (UAV). The platform is a Parrot AR.Drone 2 and uses the IEEE 802.11 protocol for command and control. The threat scenarios are the TCP and UDP Flood Attacks and the de-authentication attack. The de-authentication is a functionality available on IEEE 802.11 Wireless protocol that is misused for DoS attacks. The approach for DoS classification is based on logistic regression and decision tree (DT) using a dataset composed of malicious and normal network traffic captured during UAV flights. The DT model obtained in this paper accomplishes an F1-score to classify DoS attacks (de-authentication, UDP, and TCP flood) of 0.97.","PeriodicalId":376642,"journal":{"name":"2021 10th Latin-American Symposium on Dependable Computing (LADC)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Classification of Denial of Service Attacks on Wi-Fi-based Unmanned Aerial Vehicle\",\"authors\":\"G. Bertoli, L. A. P. Júnior, O. Saotome\",\"doi\":\"10.1109/ladc53747.2021.9672561\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an analysis of denial of service (DoS) attacks on Wi-Fi-based Unmanned Aerial Vehicle (UAV). The platform is a Parrot AR.Drone 2 and uses the IEEE 802.11 protocol for command and control. The threat scenarios are the TCP and UDP Flood Attacks and the de-authentication attack. The de-authentication is a functionality available on IEEE 802.11 Wireless protocol that is misused for DoS attacks. The approach for DoS classification is based on logistic regression and decision tree (DT) using a dataset composed of malicious and normal network traffic captured during UAV flights. The DT model obtained in this paper accomplishes an F1-score to classify DoS attacks (de-authentication, UDP, and TCP flood) of 0.97.\",\"PeriodicalId\":376642,\"journal\":{\"name\":\"2021 10th Latin-American Symposium on Dependable Computing (LADC)\",\"volume\":\"56 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 10th Latin-American Symposium on Dependable Computing (LADC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ladc53747.2021.9672561\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 10th Latin-American Symposium on Dependable Computing (LADC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ladc53747.2021.9672561","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Classification of Denial of Service Attacks on Wi-Fi-based Unmanned Aerial Vehicle
This paper presents an analysis of denial of service (DoS) attacks on Wi-Fi-based Unmanned Aerial Vehicle (UAV). The platform is a Parrot AR.Drone 2 and uses the IEEE 802.11 protocol for command and control. The threat scenarios are the TCP and UDP Flood Attacks and the de-authentication attack. The de-authentication is a functionality available on IEEE 802.11 Wireless protocol that is misused for DoS attacks. The approach for DoS classification is based on logistic regression and decision tree (DT) using a dataset composed of malicious and normal network traffic captured during UAV flights. The DT model obtained in this paper accomplishes an F1-score to classify DoS attacks (de-authentication, UDP, and TCP flood) of 0.97.