{"title":"基于众包空中交通管制数据的无同步GPS欺骗检测","authors":"Gaoyang Liu, Rui Zhang, Chen Wang, Ling Liu","doi":"10.1109/MDM.2019.00-49","DOIUrl":null,"url":null,"abstract":"GPS-dependent localization, navigation and air traffic control (ATC) applications have had a significant impact on the modern aviation industry. However, the lack of encryption and authentication makes GPS vulnerable to spoofing attacks with the purpose of hijacking aerial vehicles or threatening air safety. In this paper, we propose GPS-Probe, a GPS spoofing detection algorithm that leverages the ATC messages that are periodically broadcasted by aerial vehicles. By continuously analyzing the received signal strength indicator (RSSI) and the timestamps at server (TSS) of the ATC messages, which are monitored by multiple ground sensors, GPS-Probe constructs a machine learning enabled framework to estimate the real position of the target aerial vehicle and to detect whether or not the position data is compromised by GPS spoofing attacks. Unlike existing techniques, GPS-Probe neither requires any updates of the GPS infrastructure nor updates of the GPS receivers. More importantly, it releases the requirement on time synchronization of the ground sensors distributed around the world. Using the real-world ATC data crowdsourced by the OpenSky Network, our experiment results show that GPS-Probe can achieve the detection accuracy and precision, of 81.7% and 85.3% respectively on average, and up to 89.7% and 91.5% respectively at the best.","PeriodicalId":241426,"journal":{"name":"2019 20th IEEE International Conference on Mobile Data Management (MDM)","volume":"308 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Synchronization-Free GPS Spoofing Detection with Crowdsourced Air Traffic Control Data\",\"authors\":\"Gaoyang Liu, Rui Zhang, Chen Wang, Ling Liu\",\"doi\":\"10.1109/MDM.2019.00-49\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"GPS-dependent localization, navigation and air traffic control (ATC) applications have had a significant impact on the modern aviation industry. However, the lack of encryption and authentication makes GPS vulnerable to spoofing attacks with the purpose of hijacking aerial vehicles or threatening air safety. In this paper, we propose GPS-Probe, a GPS spoofing detection algorithm that leverages the ATC messages that are periodically broadcasted by aerial vehicles. By continuously analyzing the received signal strength indicator (RSSI) and the timestamps at server (TSS) of the ATC messages, which are monitored by multiple ground sensors, GPS-Probe constructs a machine learning enabled framework to estimate the real position of the target aerial vehicle and to detect whether or not the position data is compromised by GPS spoofing attacks. Unlike existing techniques, GPS-Probe neither requires any updates of the GPS infrastructure nor updates of the GPS receivers. More importantly, it releases the requirement on time synchronization of the ground sensors distributed around the world. Using the real-world ATC data crowdsourced by the OpenSky Network, our experiment results show that GPS-Probe can achieve the detection accuracy and precision, of 81.7% and 85.3% respectively on average, and up to 89.7% and 91.5% respectively at the best.\",\"PeriodicalId\":241426,\"journal\":{\"name\":\"2019 20th IEEE International Conference on Mobile Data Management (MDM)\",\"volume\":\"308 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 20th IEEE International Conference on Mobile Data Management (MDM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MDM.2019.00-49\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 20th IEEE International Conference on Mobile Data Management (MDM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MDM.2019.00-49","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Synchronization-Free GPS Spoofing Detection with Crowdsourced Air Traffic Control Data
GPS-dependent localization, navigation and air traffic control (ATC) applications have had a significant impact on the modern aviation industry. However, the lack of encryption and authentication makes GPS vulnerable to spoofing attacks with the purpose of hijacking aerial vehicles or threatening air safety. In this paper, we propose GPS-Probe, a GPS spoofing detection algorithm that leverages the ATC messages that are periodically broadcasted by aerial vehicles. By continuously analyzing the received signal strength indicator (RSSI) and the timestamps at server (TSS) of the ATC messages, which are monitored by multiple ground sensors, GPS-Probe constructs a machine learning enabled framework to estimate the real position of the target aerial vehicle and to detect whether or not the position data is compromised by GPS spoofing attacks. Unlike existing techniques, GPS-Probe neither requires any updates of the GPS infrastructure nor updates of the GPS receivers. More importantly, it releases the requirement on time synchronization of the ground sensors distributed around the world. Using the real-world ATC data crowdsourced by the OpenSky Network, our experiment results show that GPS-Probe can achieve the detection accuracy and precision, of 81.7% and 85.3% respectively on average, and up to 89.7% and 91.5% respectively at the best.