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On the privacy offered by (k,δ )-anonymity

机译:关于(k,δ)-匿名提供的隐私

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摘要

The widespread deployment of technologies with tracking capabilities, like GPS, GSM, RFID and on-line social networks, allows mass collection of spatio-temporal data about their users. As a consequence, several methods aimed at anonymizing spatio-temporal data before their publication have been proposed in recent years. Such methods are based on a number of underlying privacy models. Among these models, (k,δ)-anonymity claims to extend the widely used fc-anonymity concept by exploiting the spatial uncertainty δ ≥ 0 in the trajectory recording process. In this paper, we prove that, for any δ≥ 0 (that is, whenever there is actual uncertainty), (k,δ)-anonymity does not offer trajectory k-anonymity, that is, it does not hide an original trajectory in a set of k indistinguishable anonymized trajectories. Hence, the methods based on (k,δ)-anonymity, like Never Walk Alone (NWA) and Wait For Me (W4M) can offer trajectory fc-anonymity only when δ= 0 (no uncertainty). Thus, the idea of exploiting the recording uncertainty δ to achieve trajectory k-anonymity with information loss inversely proportional to δ turns out to be flawed.
机译:具有跟踪功能的技术的广泛部署,例如GPS,GSM,RFID和在线社交网络,可以大规模收集有关其用户的时空数据。结果,近年来已经提出了几种旨在使时空数据匿名化的方法。这样的方法基于许多潜在的隐私模型。在这些模型中,(k,δ)匿名声称通过在轨迹记录过程中利用空间不确定性δ≥0来扩展广泛使用的fc匿名概念。本文证明,对于任何δ≥0(即存在实际不确定性的情况),(k,δ)-匿名性不会提供轨迹k-匿名性,也就是说,它不会隐藏原始轨迹一组k个无法区分的匿名轨迹。因此,仅当δ= 0(无不确定性)时,基于(k,δ)匿名性的方法(例如,从不单独行走(NWA)和等待我(W4M))才能提供轨迹fc匿名性。因此,利用记录不确定性δ来实现轨迹k匿名性而使信息损失与δ成反比的想法是有缺陷的。

著录项

  • 来源
    《Information Systems》 |2013年第4期|491-494|共4页
  • 作者单位

    Universitat Rovira i Virgili, Department of Computer Engineering and Mathematics, UNESCO Chair in Data Privacy, Av. Paiesos Catalans 26, E-43007 Tarragona, Catalonia;

    Universitat Rovira i Virgili, Department of Computer Engineering and Mathematics, UNESCO Chair in Data Privacy, Av. Paiesos Catalans 26, E-43007 Tarragona, Catalonia;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    spatio-temporal data; trajectory; data privacy; anonymity; uncertainty;

    机译:时空数据弹道;数据隐私;匿名;不确定;
  • 入库时间 2022-08-18 02:47:54

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