SaTC: CORE: Small: Customizable Geo-Obfuscation to Protect Users' Location Privacy in Mobile Crowdsourcing

SaTC:核心:小型:可定制的地理混淆以保护移动众包中用户的位置隐私

基本信息

  • 批准号:
    2313866
  • 负责人:
  • 金额:
    $ 34.5万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-07-01 至 2026-06-30
  • 项目状态:
    未结题

项目摘要

Geo-obfuscation is a privacy protection technique that allows users to report obfuscated locations instead of their precise locations in location-based applications such as mobile crowdsourcing. While geo-obfuscation offers strong privacy guarantees, the location errors that arise due to obfuscation can affect the quality of the service. Current research on this topic focuses on minimizing quality loss through optimization techniques, but due to the high computation overhead, it is limited to a small number of locations. Consequently, existing works restrict the scope of geo-obfuscation to either low granularity in a large-scale region or high granularity in a small-scale region, leaving little room for users to customize geo-obfuscation to their specific requirements. The project's novelties are to design a user-centric geo-obfuscation in multi-granularity and multi-scale, which can be customized based on users' diverse demands. The proposed research significantly enhances the flexibility and scalability of existing geo-obfuscation techniques, thereby advancing their application in various mobile contexts. The project's broader significance and importance are to positively impact the wide adoption of many advanced crowdsourcing applications while ensuring individual privacy. In addition, the educational efforts of this project encompass curriculum development, K-12 outreach activities, and the engagement of underrepresented students in research.The project comprises three research tasks. Firstly, the project designs time-efficient algorithms capable of calculating geo-obfuscation for a wide range of location granularity and scales, covering millions of locations in a hierarchy that includes counties, cities, streets, buildings, and rooms. Secondly, based on the developed geo-obfuscation algorithms, the project aims to customize geo-obfuscation according to the demands of a large group of mobile users, taking into account their diverse mobility features and contextual information across different scenarios. Finally, the project identifies potential threats to customizable geo-obfuscation at various granularity levels. On the basis of the insights gained from the threat models, the project designs countermeasures to better protect users' location privacy against the new threats.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Geo-Obfuscation是一种隐私保护技术,允许用户在基于位置的应用程序(例如移动众包)中报告混淆的位置,而不是其精确位置。尽管Geo-Obfuscation提供了强大的隐私保证,但由于混淆而引起的位置错误可能会影响服务的质量。当前对该主题的研究重点是通过优化技术最大程度地减少质量损失,但是由于开销高的计算,它仅限于少数位置。因此,现有的作品将地理浮肿的范围限制在大型地区的低粒度或小型地区的高粒度范围内,用户几乎没有空间来根据其特定要求自定义地理斑点。该项目的新颖性是设计以用户为中心的多范围和多规模的地理刺激,可以根据用户的多样需求来自定义。拟议的研究大大提高了现有的地理粘附技术的灵活性和可扩展性,从而在各种移动环境中提高了它们的应用。该项目的更广泛的意义和重要性是在确保个人隐私的同时,积极影响许多高级众包应用程序的广泛采用。此外,该项目的教育工作包括课程开发,K-12外展活动以及代表性不足的学生在研究中的参与。该项目包括三项研究任务。首先,该项目设计了能够计算出广泛位置粒度和尺度的地理掩埋的耗时算法,涵盖了包括县,城市,街道,建筑物和房间的等级结构中数百万个位置。其次,基于开发的地理粘连算法,该项目旨在根据大量移动用户的需求来自定义地理覆盖,并考虑到其各种情况跨不同情况的各种移动性功能和上下文信息。最后,该项目确定了在各种粒度水平上对可定制的地理掺杂的潜在威胁。根据从威胁模型中获得的见解,该项目设计对策,以更好地保护用户的位置隐私,以抵御新的威胁。该奖项反映了NSF的法定任务,并被认为是通过基金会的知识分子优点和更广泛的影响来评估的评估值得支持的。

项目成果

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Chenxi Qiu其他文献

A Time-Efficient Strategy For Relay Selection and Link Scheduling In Wireless Communication Networks
无线通信网络中中继选择和链路调度的省时策略
  • DOI:
  • 发表时间:
    2015
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Chenxi Qiu
  • 通讯作者:
    Chenxi Qiu
Enhancing Scalability of Metric Differential Privacy via Secret Dataset Partitioning and Benders Decomposition
  • DOI:
    10.48550/arxiv.2405.04344
  • 发表时间:
    2024-05
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Chenxi Qiu
  • 通讯作者:
    Chenxi Qiu
An Efficient Wireless Power Transfer System to Balance the State of Charge of Electric Vehicles
平衡电动汽车充电状态的高效无线电力传输系统
Link Scheduling in Cooperative Communication with SINR-Based Interference
基于SINR干扰的协作通信中的链路调度
Towards Green Transportation: Fast Vehicle Velocity Optimization for Fuel Efficiency
迈向绿色交通:快速车辆速度优化以提高燃油效率

Chenxi Qiu的其他文献

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{{ truncateString('Chenxi Qiu', 18)}}的其他基金

Collaborative Research: SaTC: CORE: Small: Privacy protection of Vehicles location in Spatial Crowdsourcing under realistic adversarial models
合作研究:SaTC:核心:小:现实对抗模型下空间众包中车辆位置的隐私保护
  • 批准号:
    2136948
  • 财政年份:
    2021
  • 资助金额:
    $ 34.5万
  • 项目类别:
    Standard Grant
Collaborative Research: SaTC: CORE: Small: Privacy protection of Vehicles location in Spatial Crowdsourcing under realistic adversarial models
合作研究:SaTC:核心:小:现实对抗模型下空间众包中车辆位置的隐私保护
  • 批准号:
    2029881
  • 财政年份:
    2021
  • 资助金额:
    $ 34.5万
  • 项目类别:
    Standard Grant

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相似海外基金

SaTC: CORE: Small: An evaluation framework and methodology to streamline Hardware Performance Counters as the next-generation malware detection system
SaTC:核心:小型:简化硬件性能计数器作为下一代恶意软件检测系统的评估框架和方法
  • 批准号:
    2327427
  • 财政年份:
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  • 资助金额:
    $ 34.5万
  • 项目类别:
    Continuing Grant
Collaborative Research: NSF-BSF: SaTC: CORE: Small: Detecting malware with machine learning models efficiently and reliably
协作研究:NSF-BSF:SaTC:核心:小型:利用机器学习模型高效可靠地检测恶意软件
  • 批准号:
    2338301
  • 财政年份:
    2024
  • 资助金额:
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  • 项目类别:
    Continuing Grant
Collaborative Research: NSF-BSF: SaTC: CORE: Small: Detecting malware with machine learning models efficiently and reliably
协作研究:NSF-BSF:SaTC:核心:小型:利用机器学习模型高效可靠地检测恶意软件
  • 批准号:
    2338302
  • 财政年份:
    2024
  • 资助金额:
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SaTC: CORE: Small: NSF-DST: Understanding Network Structure and Communication for Supporting Information Authenticity
SaTC:核心:小型:NSF-DST:了解支持信息真实性的网络结构和通信
  • 批准号:
    2343387
  • 财政年份:
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NSF-NSERC: SaTC: CORE: Small: Managing Risks of AI-generated Code in the Software Supply Chain
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  • 批准号:
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  • 财政年份:
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  • 资助金额:
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