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Untangling RFID Privacy Models

机译:解开RFID隐私模型

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摘要

The rise of wireless applications based on RFID has brought up major concerns on privacy. Indeed nowadays, when such an application is deployed, informed customers yearn for guarantees that their privacy will not be threatened. One formal way to perform this task is to assess the privacy level of the RFID application with a model. However, if the chosen model does not reflect the assumptions and requirements of the analyzed application, it may misevaluate its privacy level. Therefore, selecting the most appropriate model among all the existing ones is not an easy task. This paper investigates the eight most well-known RFID privacy models and thoroughly examines their advantages and drawbacks in three steps. Firstly, five RFID authentication protocols are analyzed with these models. This discloses a main worry: although these protocols intuitively ensure different privacy levels, no model is able to accurately distinguish them. Secondly, these models are grouped according to their features (e.g., tag corruption ability). This classification reveals the most appropriate candidate model(s) to be used for a privacy analysis when one of these features is especially required. Furthermore, it points out that none of the models are comprehensive. Hence, some combinations of features may not match any model. Finally, the privacy properties of the eight models are compared in order to provide an overall view of their relations. This part highlights that no model globally outclasses the other ones. Considering the required properties of an application, the thorough study provided in this paper aims to assist system designers to choose the best suited model.
机译:基于RFID的无线应用的兴起引起了人们对隐私的关注。确实,如今,当部署了这样的应用程序时,知情的客户渴望获得保证其隐私不会受到威胁的保证。执行此任务的一种正式方法是使用模型评估RFID应用程序的隐私级别。但是,如果所选模型不能反映所分析应用程序的假设和要求,则可能会错误评估其隐私级别。因此,在所有现有模型中选择最合适的模型并非易事。本文研究了八个最著名的RFID隐私模型,并分三个步骤全面研究了它们的优缺点。首先,利用这些模型分析了五种RFID认证协议。这揭示了一个主要问题:尽管这些协议直观地确保了不同的隐私级别,但是没有模型能够准确区分它们。其次,这些模型根据其功能(例如,标记破坏能力)进行分组。当特别需要这些功能之一时,此分类将显示用于隐私分析的最合适的候选模型。此外,它指出没有一个模型是全面的。因此,某些特征组合可能与任何模型都不匹配。最后,比较八个模型的隐私属性,以提供它们之间关系的整体视图。本部分强调,没有任何一个模型能在整体上超越其他模型。考虑到应用程序所需的属性,本文提供的深入研究旨在帮助系统设计人员选择最适合的模型。

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  • 来源
    《Journal of computer networks and communications》 |2013年第2013期|710275.1-710275.26|共26页
  • 作者

    Iwen Coisel; Tania Martin;

  • 作者单位

    ICTEAM/Crypto Group and ICTEAM/GSI, Universite Catholique de Louvain, 1348 Louvain-la-Neuve, Belgium;

    ICTEAM/Crypto Group and ICTEAM/GSI, Universite Catholique de Louvain, 1348 Louvain-la-Neuve, Belgium;

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