{"title":"未来车载网络中的位置信息验证","authors":"Waheeda Jabbar, R. Malaney, Shihao Yan","doi":"10.1109/CAVS51000.2020.9334684","DOIUrl":null,"url":null,"abstract":"In vehicular networks, vehicle claimed positions should be independently verified to help protect the wider network against location-spoofing attacks. In this work, we propose a new solution to the problem of location verification using the Cramer-Rao Bound (CRB) on location accuracy. Compared to known-optimal solutions, our technique has the advantage that it does not depend on a priori information on the probability of any vehicle being malicious. To analyze the performance of our new solution, we compare its operation, under Received Signal Strength (RSS) inputs, with a known optimal solution for this problem that assumes the probability of a vehicle being malicious is known. The results show that our new solution provides close to optimal performance over a wide range of anticipated channel conditions. Our solution is simple to deploy and can easily be integrated into a host of vehicular applications that use location information as an input.","PeriodicalId":409507,"journal":{"name":"2020 IEEE 3rd Connected and Automated Vehicles Symposium (CAVS)","volume":"145 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Location Information Verification in Future Vehicular Networks\",\"authors\":\"Waheeda Jabbar, R. Malaney, Shihao Yan\",\"doi\":\"10.1109/CAVS51000.2020.9334684\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In vehicular networks, vehicle claimed positions should be independently verified to help protect the wider network against location-spoofing attacks. In this work, we propose a new solution to the problem of location verification using the Cramer-Rao Bound (CRB) on location accuracy. Compared to known-optimal solutions, our technique has the advantage that it does not depend on a priori information on the probability of any vehicle being malicious. To analyze the performance of our new solution, we compare its operation, under Received Signal Strength (RSS) inputs, with a known optimal solution for this problem that assumes the probability of a vehicle being malicious is known. The results show that our new solution provides close to optimal performance over a wide range of anticipated channel conditions. Our solution is simple to deploy and can easily be integrated into a host of vehicular applications that use location information as an input.\",\"PeriodicalId\":409507,\"journal\":{\"name\":\"2020 IEEE 3rd Connected and Automated Vehicles Symposium (CAVS)\",\"volume\":\"145 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 3rd Connected and Automated Vehicles Symposium (CAVS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CAVS51000.2020.9334684\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 3rd Connected and Automated Vehicles Symposium (CAVS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAVS51000.2020.9334684","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Location Information Verification in Future Vehicular Networks
In vehicular networks, vehicle claimed positions should be independently verified to help protect the wider network against location-spoofing attacks. In this work, we propose a new solution to the problem of location verification using the Cramer-Rao Bound (CRB) on location accuracy. Compared to known-optimal solutions, our technique has the advantage that it does not depend on a priori information on the probability of any vehicle being malicious. To analyze the performance of our new solution, we compare its operation, under Received Signal Strength (RSS) inputs, with a known optimal solution for this problem that assumes the probability of a vehicle being malicious is known. The results show that our new solution provides close to optimal performance over a wide range of anticipated channel conditions. Our solution is simple to deploy and can easily be integrated into a host of vehicular applications that use location information as an input.