{"title":"A novel secured traffic monitoring system for VANET","authors":"S. Taie, Sanaa Taha","doi":"10.1109/PERCOMW.2017.7917553","DOIUrl":null,"url":null,"abstract":"There is a growing need for Vehicular Ad-hoc Networks (VANETs), in which vehicles communicate with each other (i. e., Vehicle to Vehicle, V2V) or with the infrastructure (i. e., Vehicle to Infrastructure, V2I) on a wireless basis. This paper presents an improved traffic monitoring system for VANET applications via a proposed security scheme. Specifically, the proposed model analyzes the monitored scene, and automatically generates monitoring reports, which contain the current time, current location, and traffic event type (which may be an accident, crowd, demonstration or protest events). Additionally, two schemes have been proposed: one is detecting vehicle accident using image processing techniques, and the other is detecting both transmitted fake reports about the road and the malicious car's driver, who transmits those fake reports. The security scheme achieves source authentication, data confidentiality, driver anonymity, and non-repudiation security services. Also the monitoring system achieves 85.41% average accuracy and 84.093 msec. average execution time with only 0.011% increase in computation overhead for applying the security scheme.","PeriodicalId":319638,"journal":{"name":"2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PERCOMW.2017.7917553","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
There is a growing need for Vehicular Ad-hoc Networks (VANETs), in which vehicles communicate with each other (i. e., Vehicle to Vehicle, V2V) or with the infrastructure (i. e., Vehicle to Infrastructure, V2I) on a wireless basis. This paper presents an improved traffic monitoring system for VANET applications via a proposed security scheme. Specifically, the proposed model analyzes the monitored scene, and automatically generates monitoring reports, which contain the current time, current location, and traffic event type (which may be an accident, crowd, demonstration or protest events). Additionally, two schemes have been proposed: one is detecting vehicle accident using image processing techniques, and the other is detecting both transmitted fake reports about the road and the malicious car's driver, who transmits those fake reports. The security scheme achieves source authentication, data confidentiality, driver anonymity, and non-repudiation security services. Also the monitoring system achieves 85.41% average accuracy and 84.093 msec. average execution time with only 0.011% increase in computation overhead for applying the security scheme.