PryMe, a Universal Framework to Measure the Strength of Privacy-enhancing Technologies

PryMe,衡量隐私增强技术强度的通用框架

基本信息

  • 批准号:
    EP/P006752/1
  • 负责人:
  • 金额:
    $ 11.29万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 财政年份:
    2017
  • 资助国家:
    英国
  • 起止时间:
    2017 至 无数据
  • 项目状态:
    已结题

项目摘要

Privacy is a universal value and an important matter of human rights, security, and freedom of expression. However, in the digital era privacy is increasingly becoming eroded, and existing protections in terms of laws and privacy policies turn out to be insufficient because they do not prevent privacy violations from happening. In contrast, privacy protections on a technical level, so-called privacy-enhancing technologies, can prevent privacy violations and are thus a topic of much current research.One way to show how effective new privacy-enhancing technologies are, i.e. to what extent they are able to protect privacy, is to use privacy metrics to measure the amount of privacy the technologies provide. Even though many privacy metrics have been proposed, there are many studies showing their shortcomings in terms of consistency, reproducibility, and applicability in different application domains. This is an important issue because use of a weak privacy metric can lead to real-world privacy violations if the privacy metric overestimates the amount of privacy provided by a technology.The proposed research addresses this issue by evaluating the quality of existing privacy metrics, identifying their strengths and weaknesses, and building on this evidence to propose new, much stronger privacy metrics. Our aim is to create novel privacy metrics that measure the effectiveness of privacy-enhancing technologies consistently, reproducibly, and across application domains. To achieve this aim, we will (i) create the modular framework PryMe for the systematic evaluation of privacy metrics, (ii) apply the PryMe framework to evaluate privacy metrics across application domains, and (iii) propose strong new privacy metrics that work in each application domain. By proposing a single framework to evaluate privacy metrics in many application domains, we allow research ideas on privacy metrics from different domains to complement each other, which will transform how privacy is measured. To further this transformation, we will release open source code for the PryMe framework to enable other researchers to study different application domains and new privacy metrics. In the long term, this will be relevant to improve privacy-enhancing technologies, and thereby improve privacy for end users.Privacy measurement is important not only to improve privacy-enhancing technologies, but also to analyse trade-offs between privacy and data utility, or between privacy and security. Better privacy metrics therefore not only improve privacy for end users, but also improve the decision-making in situations when privacy needs to be weighed against utility or security. Better privacy metrics can also help improve the user acceptance of new technologies such as vehicular networks and smart homes by showing that privacy issues have been addressed on a technical level.
隐私是一种普世价值,也是人权、安全和表达自由的重要问题。然而,在数字时代,隐私越来越受到侵蚀,现有的法律和隐私政策保护是不够的,因为它们不能防止侵犯隐私的行为发生。与此相反,技术层面的隐私保护,即所谓的隐私增强技术,可以防止侵犯隐私,因此是当前研究的一个主题。要显示新的隐私增强技术的有效性,即它们能够在多大程度上保护隐私,一种方法是使用隐私指标来衡量技术提供的隐私量。尽管已经提出了许多隐私度量,但许多研究表明它们在不同应用领域的一致性,可重复性和适用性方面存在不足。这是一个重要的问题,因为如果隐私度量高估了技术提供的隐私量,那么使用弱隐私度量可能会导致现实世界的隐私侵犯。拟议的研究通过评估现有隐私度量的质量来解决这个问题,确定它们的优点和缺点,并在此基础上提出新的,更强大的隐私度量。我们的目标是创建新的隐私指标,以一致、可重复和跨应用领域的方式衡量隐私增强技术的有效性。为了实现这一目标,我们将(i)创建模块化框架PryMe,用于系统地评估隐私指标,(ii)应用PryMe框架来评估跨应用领域的隐私指标,以及(iii)提出适用于每个应用领域的强大的新隐私指标。通过提出一个单一的框架来评估许多应用领域的隐私指标,我们允许不同领域的隐私指标的研究思路,以相互补充,这将改变隐私的测量方式。为了进一步推进这一转变,我们将发布PryMe框架的开源代码,以使其他研究人员能够研究不同的应用领域和新的隐私指标。从长远来看,这将有助于改善隐私增强技术,从而改善最终用户的隐私。隐私测量不仅对改善隐私增强技术很重要,而且对分析隐私和数据效用之间或隐私和安全之间的权衡也很重要。因此,更好的隐私指标不仅可以改善最终用户的隐私,还可以在需要权衡隐私与实用性或安全性的情况下改善决策。更好的隐私指标还可以帮助提高用户对车载网络和智能家居等新技术的接受度,表明隐私问题已经在技术层面得到了解决。

项目成果

期刊论文数量(7)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Poster
海报
  • DOI:
  • 发表时间:
    2010
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Bennett N G
  • 通讯作者:
    Bennett N G
Data Privacy Management, Cryptocurrencies and Blockchain Technology - ESORICS 2018 International Workshops, DPM 2018 and CBT 2018, Barcelona, Spain, September 6-7, 2018, Proceedings
数据隐私管理、加密货币和区块链技术 - ESORICS 2018 国际研讨会、DPM 2018 和 CBT 2018,西班牙巴塞罗那,2018 年 9 月 6-7 日,会议记录
  • DOI:
    10.1007/978-3-030-00305-0_17
  • 发表时间:
    2018
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Wagner I
  • 通讯作者:
    Wagner I
On the Strength of Privacy Metrics for Vehicular Communication
  • DOI:
    10.1109/tmc.2018.2830359
  • 发表时间:
    2019-02
  • 期刊:
  • 影响因子:
    7.9
  • 作者:
    Yuchen Zhao;Isabel Wagner
  • 通讯作者:
    Yuchen Zhao;Isabel Wagner
Using Metrics Suites to Improve the Measurement of Privacy in Graphs
Challenges in assessing privacy impact: Tales from the front lines
  • DOI:
    10.1002/spy2.101
  • 发表时间:
    2020-03-01
  • 期刊:
  • 影响因子:
    1.9
  • 作者:
    Ferra, Fenia;Wagner, Isabel;Snape, Richard
  • 通讯作者:
    Snape, Richard
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Isabel Wagner其他文献

What's going on at the back-end? Risks and benefits of smart toilets
后端发生了什么?
  • DOI:
    10.48550/arxiv.2308.15935
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Isabel Wagner;E. Boiten
  • 通讯作者:
    E. Boiten
Privacy Risk Assessment: From Art to Science, By Metrics
隐私风险评估:从艺术到科学,按指标
  • DOI:
  • 发表时间:
    2017
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Isabel Wagner;E. Boiten
  • 通讯作者:
    E. Boiten
Unified Communication: What do Digital Activists need?
统一沟通:数字活动家需要什么?
User Behavior Adversary strongweak Privacy Metrics Strength Indicators Evenness + — Shared Value Range + — Monotonicity
用户行为 对手 Strongweak 隐私指标 强度指标 均匀性 + — 共享值范围 + — 单调性
  • DOI:
  • 发表时间:
    2018
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Yuchen Zhao;Isabel Wagner
  • 通讯作者:
    Isabel Wagner
Designing Strong Privacy Metrics Suites Using Evolutionary Optimization
使用进化优化设计强大的隐私指标套件

Isabel Wagner的其他文献

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