III: Small: Collaborative Research: PE4GQ - Practical Encryption for Geospatial Queries on Private Data

III:小型:协作研究:PE4GQ - 私有数据地理空间查询的实用加密

基本信息

  • 批准号:
    1910950
  • 负责人:
  • 金额:
    $ 29.08万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-10-01 至 2023-09-30
  • 项目状态:
    已结题

项目摘要

The mobile computing revolution led to the emergence of novel and exciting applications centered on geospatial data, such as location-based services, geosocial networks, and ride-sharing. These apps enable users to receive services customized to their locations and to interact with nearby peers. However, recent years also witnessed a growing number of risks associated with sharing of location data. Using location information, adversaries may stage a broad spectrum of attacks, ranging from physical surveillance and stalking, to inferring private details about an individual?s health status, political or religious affiliations, alternative lifestyles, etc. The proposed project will investigate secure and efficient techniques to protect the locations of mobile users before they are sent to online services. The focus will be on encryption, which provides a high level of protection, on the same level currently used for confidential data such as social security numbers and bank account information. Location privacy is an important component of the broader online privacy concept. Strong protection for users? whereabouts will bring significant societal benefits in the current online ecosystem, where privacy attacks occur more frequently and with far greater ramifications than before, as illustrated by recent high-profile privacy breaches that affected prominent players in the social media industry (e.g., Google, Facebook, Yahoo).Several prior research efforts focused on protecting locations through mechanisms like location cloaking, differential privacy or geo-indistinguishability, but none of these existing approaches can properly address the challenges of online, continuous sharing of locations. The only direction that achieves a sufficient amount of protection is represented by cryptographic approaches, but despite recent breakthroughs in the area of functional encryption, processing on encrypted data is very slow and/or insufficiently expressive to support the use case scenarios required by location-centric applications. The objective of this project is to bridge the gap between geospatial applications on one side and functional encryption on the other. The proposed PE4GQ (Practical Encryption for Geospatial Queries) framework will allow researchers and practitioners to make use of encrypted search primitives on geospatial data with practical computational and communication overhead. The project will adopt existing functional encryption techniques and customize their use to the specific requirements of geospatial queries. The project will address several challenging tasks: (i) identifying a small set of representative plaintext operations that occur commonly in location-centric applications and can be used to express more complex spatial queries; (ii) identifying appropriate cryptographic building blocks that can be used to securely evaluate the operations identified in the first task; (iii) investigating data representations and query encodings that allow efficient secure evaluation by reducing the number of expensive cryptographic primitives; and (iv) investigating performance optimizations that reduce encrypted data processing overhead by taking into account information from the spatial domain (i.e., through cross-layer design).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.
移动计算革命导致了以地理空间数据为中心的新颖和令人兴奋的应用程序的出现,例如基于位置的服务,地理社会网络和乘车共享。这些应用程序使用户能够接收到其位置自定义的服务并与附近的同行互动。但是,近年来还见证了与共享位置数据相关的越来越多的风险。使用位置信息,对手可能会进行广泛的攻击,从物理监视和跟踪到推断有关个人健康状况,政治或宗教隶属关系的私人细节,替代生活方式等。该提议的项目将调查安全有效的技术,以便在发送到在线服务之前保护移动用户的位置。重点将放在加密上,该加密提供高水平的保护,该级别与当前用于机密数据(例如社会保险号和银行帐户信息)的相同级别。位置隐私是更广泛的在线隐私概念的重要组成部分。对用户的强大保护?如今,隐私攻击发生的频率更高和更大的后果将在当前的在线生态系统中带来巨大的社会利益,而最近的高调隐私泄露了影响社交媒体行业中著名参与者的著名参与者(例如,通过Google,Google,Facebook,Facebook,Yahoo)的位置,私有化的位置与位置相同的位置,这些努力与位置相同,并且在机构上进行了不同的范围,并且相互不同这些现有的方法可以正确解决在线,连续共享位置的挑战。获得足够的保护的唯一方向是密码方法的代表,但是尽管最近在功能加密领域取得了突破,但对加密数据的处理仍非常慢,/或不足以支持以以位置为中心的应用程序所需的用例场景。该项目的目的是弥合一侧地理空间应用之间的差距,而另一侧的功能加密。拟议的PE4GQ(用于地理空间查询的实用加密)框架将使研究人员和从业人员能够使用带有实用计算和通信开销的地理空间数据上的加密搜索原始图。该项目将采用现有的功能加密技术,并根据地理空间查询的特定要求自定义其使用。该项目将解决几个具有挑战性的任务:(i)确定通常在以位置为中心的应用程序中发生的一小部分代表性的明文操作,可用于表达更复杂的空间查询; (ii)确定可用于安全评估第一个任务中确定的操作的适当的加密构件; (iii)调查数据表示和查询编码,以减少昂贵的加密原语的数量,从而允许有效的安全评估; (iv)调查性能优化,通过考虑来自空间领域的信息(即,通过跨层设计)来减少加密数据处理开销。该奖项反映了NSF的法定任务,并被认为是值得通过基金会的知识分子优点和更广泛影响的审查标准来通过评估来通过评估来支持的。

项目成果

期刊论文数量(17)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
REACT: Real-Time Contact Tracing and Risk Monitoring via Privacy-Enhanced Mobile Tracking
REACT:通过隐私增强型移动跟踪进行实时接触者追踪和风险监控
Toward Accurate Spatiotemporal COVID-19 Risk Scores Using High-Resolution Real-World Mobility Data
Differentially-Private Publication of Origin-Destination Matrices with Intermediate Stops
  • DOI:
    10.48786/edbt.2022.04
  • 发表时间:
    2022-02
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Sina Shaham;G. Ghinita;C. Shahabi
  • 通讯作者:
    Sina Shaham;G. Ghinita;C. Shahabi
NeuroSketch: Fast and Approximate Evaluation of Range Aggregate Queries with Neural Networks
An Efficient and Secure Location-based Alert Protocol using Searchable Encryption and Huffman Codes
  • DOI:
    10.5441/002/edbt.2021.24
  • 发表时间:
    2021-05
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Sina Shaham;G. Ghinita;C. Shahabi
  • 通讯作者:
    Sina Shaham;G. Ghinita;C. Shahabi
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Cyrus Shahabi其他文献

Cyrus Shahabi的其他文献

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{{ truncateString('Cyrus Shahabi', 18)}}的其他基金

III: Small: NeuroDB: A Neural Network Framework for Efficiently Answering Database Queries Approximately
III:小:NeuroDB:一种高效回答数据库查询的神经网络框架
  • 批准号:
    2128661
  • 财政年份:
    2021
  • 资助金额:
    $ 29.08万
  • 项目类别:
    Standard Grant
RAPID: Collaborative: REACT: Real-time Contact Tracing and Risk Monitoring via Privacy-enhanced Mobile Tracking
RAPID:协作:REACT:通过隐私增强型移动跟踪进行实时接触者追踪和风险监控
  • 批准号:
    2027794
  • 财政年份:
    2020
  • 资助金额:
    $ 29.08万
  • 项目类别:
    Standard Grant
2016 IEEE Mobile Data Management (MDM 2016) Conference: Student Activities Support; Porto, Portugal; June 13-16, 2016
2016 IEEE移动数据管理(MDM 2016)会议:学生活动支持;
  • 批准号:
    1632538
  • 财政年份:
    2016
  • 资助金额:
    $ 29.08万
  • 项目类别:
    Standard Grant
BDD: Human-Centered Situational Awareness Platform for Disaster Response and Recovery
BDD:以人为本的灾难响应和恢复态势感知平台
  • 批准号:
    1461963
  • 财政年份:
    2015
  • 资助金额:
    $ 29.08万
  • 项目类别:
    Standard Grant
III: Small: GeoCrowd - A Generic Framework for Trustworthy Spatial Crowdsourcing
III:小型:GeoCrowd - 值得信赖的空间众包的通用框架
  • 批准号:
    1320149
  • 财政年份:
    2013
  • 资助金额:
    $ 29.08万
  • 项目类别:
    Standard Grant
III: Small: Real-World Traffic Data Management for Time-Dependent Spatial Queries
III:小型:用于时间相关空间查询的真实交通数据管理
  • 批准号:
    1115153
  • 财政年份:
    2011
  • 资助金额:
    $ 29.08万
  • 项目类别:
    Standard Grant
CT-ISG: Enabling Location Privacy; Moving beyond k-anonymity, cloaking and anonymizers
CT-ISG:启用位置隐私;
  • 批准号:
    0831505
  • 财政年份:
    2008
  • 资助金额:
    $ 29.08万
  • 项目类别:
    Standard Grant
SGER: Blind Evaluation of Spatial Queries with Hilbert Curves to Preserve Location Privacy
SGER:使用希尔伯特曲线对空间查询进行盲评估以保护位置隐私
  • 批准号:
    0742811
  • 财政年份:
    2007
  • 资助金额:
    $ 29.08万
  • 项目类别:
    Standard Grant
HYDRA- High Performance Data Recording Architecture for Streaming Media
HYDRA-流媒体高性能数据记录架构
  • 批准号:
    0534761
  • 财政年份:
    2006
  • 资助金额:
    $ 29.08万
  • 项目类别:
    Continuing Grant
PECASE: Management of Immersive Sensor Data Streams
PECASE:沉浸式传感器数据流的管理
  • 批准号:
    0238560
  • 财政年份:
    2003
  • 资助金额:
    $ 29.08万
  • 项目类别:
    Continuing Grant

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