Jun Han, M. Harishankar, Xiao Wang, Albert Jin Chung, P. Tague
{"title":"车队:车辆排入场的物理背景验证","authors":"Jun Han, M. Harishankar, Xiao Wang, Albert Jin Chung, P. Tague","doi":"10.1145/3032970.3032987","DOIUrl":null,"url":null,"abstract":"Truck platooning is emerging as a promising solution with many economic incentives. However, securely admitting a new vehicle into a platoon is an extremely important yet difficult task. There is no adequate method today for verifying physical arrangements of vehicles within a platoon formation. Specifically, we address the problem of a platoon ghost attack wherein an attacker spoofs presence within a platoon to gain admission and subsequently execute malicious attacks. To address such concerns, we present Convoy, a novel autonomous platoon admission scheme which binds the vehicles' digital certificates to their physical context (i.e., locality). Convoy exploits the findings that vehicles traveling together experience similar context to prove to each other over time that they are co-present. Specifically, they experience similar road (e.g., bumps and cracks) and traffic (e.g., acceleration and steering) conditions. Our approach is based on the ability for vehicles to capture this context, generate fingerprints to establish shared keys, and later bind these symmetric keys to their public keys. We design and implement the Convoy protocol and evaluate it with real-world driving data. Our implementation demonstrates that vehicles traveling in adjacent lanes can be sufficiently distinguished by their context and this can be utilized to thwart platoon ghost attacks and similar misbehavior.","PeriodicalId":309322,"journal":{"name":"Proceedings of the 18th International Workshop on Mobile Computing Systems and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"39","resultStr":"{\"title\":\"Convoy: Physical Context Verification for Vehicle Platoon Admission\",\"authors\":\"Jun Han, M. Harishankar, Xiao Wang, Albert Jin Chung, P. Tague\",\"doi\":\"10.1145/3032970.3032987\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Truck platooning is emerging as a promising solution with many economic incentives. However, securely admitting a new vehicle into a platoon is an extremely important yet difficult task. There is no adequate method today for verifying physical arrangements of vehicles within a platoon formation. Specifically, we address the problem of a platoon ghost attack wherein an attacker spoofs presence within a platoon to gain admission and subsequently execute malicious attacks. To address such concerns, we present Convoy, a novel autonomous platoon admission scheme which binds the vehicles' digital certificates to their physical context (i.e., locality). Convoy exploits the findings that vehicles traveling together experience similar context to prove to each other over time that they are co-present. Specifically, they experience similar road (e.g., bumps and cracks) and traffic (e.g., acceleration and steering) conditions. Our approach is based on the ability for vehicles to capture this context, generate fingerprints to establish shared keys, and later bind these symmetric keys to their public keys. We design and implement the Convoy protocol and evaluate it with real-world driving data. Our implementation demonstrates that vehicles traveling in adjacent lanes can be sufficiently distinguished by their context and this can be utilized to thwart platoon ghost attacks and similar misbehavior.\",\"PeriodicalId\":309322,\"journal\":{\"name\":\"Proceedings of the 18th International Workshop on Mobile Computing Systems and Applications\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-02-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"39\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 18th International Workshop on Mobile Computing Systems and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3032970.3032987\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 18th International Workshop on Mobile Computing Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3032970.3032987","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Convoy: Physical Context Verification for Vehicle Platoon Admission
Truck platooning is emerging as a promising solution with many economic incentives. However, securely admitting a new vehicle into a platoon is an extremely important yet difficult task. There is no adequate method today for verifying physical arrangements of vehicles within a platoon formation. Specifically, we address the problem of a platoon ghost attack wherein an attacker spoofs presence within a platoon to gain admission and subsequently execute malicious attacks. To address such concerns, we present Convoy, a novel autonomous platoon admission scheme which binds the vehicles' digital certificates to their physical context (i.e., locality). Convoy exploits the findings that vehicles traveling together experience similar context to prove to each other over time that they are co-present. Specifically, they experience similar road (e.g., bumps and cracks) and traffic (e.g., acceleration and steering) conditions. Our approach is based on the ability for vehicles to capture this context, generate fingerprints to establish shared keys, and later bind these symmetric keys to their public keys. We design and implement the Convoy protocol and evaluate it with real-world driving data. Our implementation demonstrates that vehicles traveling in adjacent lanes can be sufficiently distinguished by their context and this can be utilized to thwart platoon ghost attacks and similar misbehavior.