Gabriele Gambigliani Zoccoli, Francesco Pollicino, Dario Stabili, Mirco Marchetti
{"title":"SixPack v2:增强SixPack以避免VANETs中的上一代不当行为检测器","authors":"Gabriele Gambigliani Zoccoli, Francesco Pollicino, Dario Stabili, Mirco Marchetti","doi":"10.1109/NCA57778.2022.10013565","DOIUrl":null,"url":null,"abstract":"This paper proposes SixPack v2, an enhanced version of the SixPack attack that allows to evade even state-of-the-art misbehavior detection systems. As the original SixPack, SixPack v2 is a dynamic attack targeting other C-ITS entities by simulating the sudden activation of the braking system with consequent activation of the Anti-lock Braking System. SixPack v2 achieves better evasion by improving the main phases of the attack (FakeBrake, Recovery, and Rejoin) through a novel path-reconstruction algorithm that generates a more realistic representation of the real vehicle trajectory. We experimentally evaluate the evasion capabilities of SixPack v2 using the F2MD framework on the LuSTMini city scenario, and we compared the detection performance of the F2MD framework on both versions of SixPack. Results show that SixPack v2 evades detection with a significantly higher likelihood with respect to the initial version of the attack, even against the latest version of F2MD.","PeriodicalId":251728,"journal":{"name":"2022 IEEE 21st International Symposium on Network Computing and Applications (NCA)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"SixPack v2: enhancing SixPack to avoid last generation misbehavior detectors in VANETs\",\"authors\":\"Gabriele Gambigliani Zoccoli, Francesco Pollicino, Dario Stabili, Mirco Marchetti\",\"doi\":\"10.1109/NCA57778.2022.10013565\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes SixPack v2, an enhanced version of the SixPack attack that allows to evade even state-of-the-art misbehavior detection systems. As the original SixPack, SixPack v2 is a dynamic attack targeting other C-ITS entities by simulating the sudden activation of the braking system with consequent activation of the Anti-lock Braking System. SixPack v2 achieves better evasion by improving the main phases of the attack (FakeBrake, Recovery, and Rejoin) through a novel path-reconstruction algorithm that generates a more realistic representation of the real vehicle trajectory. We experimentally evaluate the evasion capabilities of SixPack v2 using the F2MD framework on the LuSTMini city scenario, and we compared the detection performance of the F2MD framework on both versions of SixPack. Results show that SixPack v2 evades detection with a significantly higher likelihood with respect to the initial version of the attack, even against the latest version of F2MD.\",\"PeriodicalId\":251728,\"journal\":{\"name\":\"2022 IEEE 21st International Symposium on Network Computing and Applications (NCA)\",\"volume\":\"92 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 21st International Symposium on Network Computing and Applications (NCA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NCA57778.2022.10013565\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 21st International Symposium on Network Computing and Applications (NCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NCA57778.2022.10013565","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
SixPack v2: enhancing SixPack to avoid last generation misbehavior detectors in VANETs
This paper proposes SixPack v2, an enhanced version of the SixPack attack that allows to evade even state-of-the-art misbehavior detection systems. As the original SixPack, SixPack v2 is a dynamic attack targeting other C-ITS entities by simulating the sudden activation of the braking system with consequent activation of the Anti-lock Braking System. SixPack v2 achieves better evasion by improving the main phases of the attack (FakeBrake, Recovery, and Rejoin) through a novel path-reconstruction algorithm that generates a more realistic representation of the real vehicle trajectory. We experimentally evaluate the evasion capabilities of SixPack v2 using the F2MD framework on the LuSTMini city scenario, and we compared the detection performance of the F2MD framework on both versions of SixPack. Results show that SixPack v2 evades detection with a significantly higher likelihood with respect to the initial version of the attack, even against the latest version of F2MD.