{"title":"Poster: PREXT: Privacy extension for Veins VANET simulator","authors":"Karim Emara","doi":"10.1109/VNC.2016.7835979","DOIUrl":null,"url":null,"abstract":"Preserving location privacy is an important aspect in vehicular ad-hoc networks. Although location privacy is thoroughly studied in the past decade, it is usually skipped in VANET simulators. In this paper, we propose a location privacy extension, PREXT, for Veins framework. Currently, PREXT supports seven privacy schemes of different approaches including silent period, context-based and cryptographic mix-zone. It can be also easily extended to include more schemes. It includes adversary modules that can eavesdrop vehicle messages and track their movements. This adversary is used in measuring the gained privacy in terms of several popular metrics such as entropy, traceability and pseudonym usage statistics. We utilize this extension to compare among different schemes in an urban scenario.","PeriodicalId":352428,"journal":{"name":"2016 IEEE Vehicular Networking Conference (VNC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"41","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Vehicular Networking Conference (VNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VNC.2016.7835979","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 41
Abstract
Preserving location privacy is an important aspect in vehicular ad-hoc networks. Although location privacy is thoroughly studied in the past decade, it is usually skipped in VANET simulators. In this paper, we propose a location privacy extension, PREXT, for Veins framework. Currently, PREXT supports seven privacy schemes of different approaches including silent period, context-based and cryptographic mix-zone. It can be also easily extended to include more schemes. It includes adversary modules that can eavesdrop vehicle messages and track their movements. This adversary is used in measuring the gained privacy in terms of several popular metrics such as entropy, traceability and pseudonym usage statistics. We utilize this extension to compare among different schemes in an urban scenario.