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

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
批准号:
1909806
负责人:
Gabriel Ghinita
金额:
$20.92万
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
项目状态:
已结题
起止时间:
2019-10-01 至 2024-09-30

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中文摘要
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英文摘要
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.
期刊论文(13)
专著(0)
科研奖励(0)
会议论文
HTF: Homogeneous Tree Framework for Differentially-Private Release of Location Data
HTF:用于位置数据的差分隐私发布的同质树框架
DOI: --
发表时间: 2021
期刊: SIGSPATIAL/GIS
影响因子: --
作者: [Sina Shaham, G. Ghinita, Ritesh Ahuja, John Krumm, C. Shahabi]
通讯作者: C. Shahabi
DOI: 10.1109/icde51399.2021.00021
发表时间: 2020-02
期刊: 2021 IEEE 37th International Conference on Data Engineering (ICDE)
影响因子: --
作者: [Sepanta Zeighami;G. Ghinita;C. Shahabi]
通讯作者: Sepanta Zeighami;G. Ghinita;C. Shahabi
Supporting secure dynamic alert zones using searchable encryption and graph embedding
使用可搜索加密和图形嵌入支持安全动态警报区域
DOI: 10.1007/s00778-023-00803-2
发表时间: 2023
期刊: The VLDB Journal
影响因子: --
作者: [Shaham, Sina, Ghinita, Gabriel, Shahabi, Cyrus]
通讯作者: Shahabi, Cyrus
DOI: 10.1145/3588701
发表时间: 2022-08
期刊: Proceedings of the ACM on Management of Data
影响因子: --
作者: [Ritesh Ahuja;Sepanta Zeighami;G. Ghinita;C. Shahabi]
通讯作者: Ritesh Ahuja;Sepanta Zeighami;G. Ghinita;C. Shahabi
12
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