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: University of Massachusetts Boston
• 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 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1909806&HistoricalAwards=false
• 关键词: III; Small; Collaborative; Research; PE4GQ

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.

移动的计算革命导致了以地理空间数据为中心的新颖而令人兴奋的应用程序的出现，例如基于位置的服务，地理社交网络和乘车共享。这些应用程序使用户能够接收为其位置定制的服务，并与附近的同行进行交互。然而，近年来也见证了与共享位置数据相关的越来越多的风险。利用位置信息，对手可能会发起广泛的攻击，从物理监视和跟踪，到推断个人的私人细节？拟议的项目将调查安全和有效的技术，以保护移动的用户的位置之前，他们被发送到在线服务。重点将放在加密上，它提供了高水平的保护，与目前用于社会安全号码和银行账户信息等机密数据的保护水平相同。位置隐私是更广泛的在线隐私概念的重要组成部分。为用户提供强有力的保护。行踪将在当前的在线生态系统中带来显著的社会效益，在当前的在线生态系统中，隐私攻击比以前更频繁地发生并且具有更大的后果，如最近影响社交媒体行业中的突出参与者的备受瞩目的隐私泄露所示（例如，谷歌、Facebook、雅虎）。之前的几项研究工作都集中在通过位置隐藏、差异隐私或地理不可区分性等机制来保护位置，但这些现有方法都无法正确解决在线、持续共享位置的挑战。实现足够量的保护的唯一方向由加密方法表示，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非常缓慢和/或不足以表达以位置为中心的应用所需的用例场景。该项目的目标是弥合地理空间应用与功能加密之间的差距。拟议的PE 4GQ（实用加密地理空间数据库）框架将允许研究人员和从业人员利用加密的搜索基元的地理空间数据与实际的计算和通信开销。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具体要求对其进行定制。该项目将处理几项具有挑战性的任务：㈠确定一小部分通常在以位置为中心的应用程序中出现并可用于表达更复杂的空间查询的代表性明文操作; ㈡确定可用于安全评估第一项任务中确定的操作的适当密码构建块;（iii）研究数据表示和查询编码，通过减少昂贵的密码原语的数量，实现有效的安全评估;以及（iv）通过考虑来自空间域的信息（即，该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

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

• 发表时间: 2021
• 期刊: SIGSPATIAL/GIS
• 作者: Sina Shaham;G. Ghinita;Ritesh Ahuja;John Krumm;C. Shahabi
• 通讯作者: C. Shahabi

Secure Dynamic Skyline Queries Using Result Materialization

• DOI: 10.1109/icde51399.2021.00021
• 发表时间: 2020-02
• 期刊: 2021 IEEE 37th International Conference on Data Engineering (ICDE)
• 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
• 作者: Shaham, Sina;Ghinita, Gabriel;Shahabi, Cyrus
• 通讯作者: Shahabi, Cyrus

A Neural Approach to Spatio-Temporal Data Release with User-Level Differential Privacy

• DOI: 10.1145/3588701
• 发表时间: 2022-08
• 期刊: Proceedings of the ACM on Management of Data
• 作者: Ritesh Ahuja;Sepanta Zeighami;G. Ghinita;C. Shahabi

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
• 作者: Sina Shaham;G. Ghinita;C. Shahabi