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Improving Privacy with Intelligent Cooperative Caching in Vehicular Ad Hoc Networks

机译:通过车载Ad Hoc网络中的智能协作缓存改善隐私

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摘要

With the issuance of the Notice of Proposed Rule Making (NPRM) for Vehicle to Vehicle (V2V) communications by the United States National Highway Traffic Safety Administration (NHTSA), the goal of the widespread deployment of vehicular networking has taken a significant step towards becoming a reality. In order for consumers to accept the technology, it is expected that reasonable mechanisms will be in place to protect their privacy. Cooperative Caching has been proposed as an approach that can be used to improve privacy by distributing data items throughout the mobile network as they are requested. With this approach, vehicles first attempt to retrieve data items from the mobile network, alleviating the need to send all requests to a centralized location that may be vulnerable to an attack. However, with this approach, a requesting vehicle may expose itself to many unknown vehicles as part of the cache discovery process.;In this work we present a Public Key Infrastructure (PKI) based Cooperative Caching system that utilizes a genetic algorithm to selectively choose members of the mobile network to query for data items with a focus on improving overall privacy. The privacy improvement is achieved by avoiding those members that present a greater risk of exposing information related to the request and choosing members that have a greater potential of having the needed data item. An Agent Based Model is utilized to baseline the privacy concerns when using a broadcast based approach to cache discovery. In addition, an epidemiology inspired mathematical model is presented to illustrate the impact of reducing the number of vehicles queried during cache discovery. Periodic reports from neighboring vehicles are used by the genetic algorithm to identify which neighbors should be queried during cache discovery. In order for the system to be realistic, vehicles must trust the information in these reports. A PKI based approach used to evaluate the trustworthiness of each vehicle in the system is also detailed. We have conducted an in-depth performance study of our system that demonstrates a significant reduction in the overall risk of exposure when compared to broadcasting the request to all neighbors.
机译:随着美国国家公路交通安全管理局(NHTSA)发布《关于车辆对车辆(V2V)通信的拟议规则制定通知(NPRM)》,广泛部署车辆网络的目标迈出了重要一步一个现实。为了使消费者能够接受该技术,预计将建立合理的机制来保护其隐私。已经提出了协作缓存作为一种方法,该方法可用于通过按要求在整个移动网络中分布数据项来提高隐私性。使用这种方法,车辆首先尝试从移动网络检索数据项,从而减少了将所有请求发送到可能容易受到攻击的集中位置的需求。但是,通过这种方法,请求的车辆可能会在高速缓存发现过程中将自己暴露给许多未知的车辆。在这项工作中,我们提出了一种基于公共密钥基础结构(PKI)的协作缓存系统,该系统利用遗传算法来选择性地选择成员。移动网络查询数据项,重点是改善整体隐私。通过避免那些具有更大风险暴露与请求有关的信息的成员并选择具有更大潜力来拥有所需数据项的成员,可以实现隐私改善。当使用基于广播的方法进行缓存发现时,可以使用基于代理的模型来确定隐私问题的基准。此外,提出了一种流行病学启发的数学模型,以说明减少缓存发现期间查询的车辆数量的影响。遗传算法使用来自相邻车辆的定期报告来识别在缓存发现期间应查询哪些邻居。为了使该系统切实可行,车辆必须信任这些报告中的信息。还详细介绍了一种基于PKI的方法,用于评估系统中每辆车的可信赖性。我们已经对我们的系统进行了深入的性能研究,结果表明,与向所有邻居广播请求相比,可以大大降低总体暴露风险。

著录项

  • 作者

    Glass, Stephen C.;

  • 作者单位

    Florida Atlantic University.;

  • 授予单位 Florida Atlantic University.;
  • 学科 Computer engineering.;Engineering.
  • 学位 Ph.D.
  • 年度 2017
  • 页码 201 p.
  • 总页数 201
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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