J. Monteuuis, Aymen Boudguiga, Jun Zhang, H. Labiod, Alain Servel, P. Urien
{"title":"安全汽车风险分析方法","authors":"J. Monteuuis, Aymen Boudguiga, Jun Zhang, H. Labiod, Alain Servel, P. Urien","doi":"10.1145/3198458.3198465","DOIUrl":null,"url":null,"abstract":"Connected and automated vehicles aim to improve the comfort and the safety of the driver and passengers. To this end, car manufacturers continually improve actual standardized methods to ensure their customers safety, privacy, and vehicles security. However, these methods do not support fully autonomous vehicles, linkability and confusion threats. To address such gaps, we propose a systematic threat analysis and risk assessment framework, SARA, which comprises an improved threat model, a new attack method/asset map, the involvement of the attacker in the attack tree, and a new driving system observation metric. Finally, we demonstrate its feasibility in assessing risk with two use cases: Vehicle Tracking and Comfortable Emergency Brake Failure.","PeriodicalId":296635,"journal":{"name":"Proceedings of the 4th ACM Workshop on Cyber-Physical System Security","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":"{\"title\":\"SARA: Security Automotive Risk Analysis Method\",\"authors\":\"J. Monteuuis, Aymen Boudguiga, Jun Zhang, H. Labiod, Alain Servel, P. Urien\",\"doi\":\"10.1145/3198458.3198465\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Connected and automated vehicles aim to improve the comfort and the safety of the driver and passengers. To this end, car manufacturers continually improve actual standardized methods to ensure their customers safety, privacy, and vehicles security. However, these methods do not support fully autonomous vehicles, linkability and confusion threats. To address such gaps, we propose a systematic threat analysis and risk assessment framework, SARA, which comprises an improved threat model, a new attack method/asset map, the involvement of the attacker in the attack tree, and a new driving system observation metric. Finally, we demonstrate its feasibility in assessing risk with two use cases: Vehicle Tracking and Comfortable Emergency Brake Failure.\",\"PeriodicalId\":296635,\"journal\":{\"name\":\"Proceedings of the 4th ACM Workshop on Cyber-Physical System Security\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"29\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 4th ACM Workshop on Cyber-Physical System Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3198458.3198465\",\"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 4th ACM Workshop on Cyber-Physical System Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3198458.3198465","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Connected and automated vehicles aim to improve the comfort and the safety of the driver and passengers. To this end, car manufacturers continually improve actual standardized methods to ensure their customers safety, privacy, and vehicles security. However, these methods do not support fully autonomous vehicles, linkability and confusion threats. To address such gaps, we propose a systematic threat analysis and risk assessment framework, SARA, which comprises an improved threat model, a new attack method/asset map, the involvement of the attacker in the attack tree, and a new driving system observation metric. Finally, we demonstrate its feasibility in assessing risk with two use cases: Vehicle Tracking and Comfortable Emergency Brake Failure.