CCSS: Collaborative Research: Towards Privacy-Preserving Mobile Crowd Sensing: A Multi-Stage Solution
CCSS:协作研究:迈向保护隐私的移动人群感知:多阶段解决方案
基本信息
- 批准号:1710996
- 负责人:
- 金额:$ 15万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-07-01 至 2019-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Mobile devices, including smartphones and tablets, are becoming extremely prevalent nowadays. Equipped with diverse sensors, from GPS to camera, and paired with the inherent mobility of their owners, mobile devices are capable of acquiring rich information of surrounding environment. However, the wide adoption of mobile crowd sensing is largely hindered by its privacy concerns. To facilitate the functionality of each stage of mobile crowd sensing, including sensing task allocation, sensing data collection, and result aggregation, sensing devices report their location information, sensing capabilities, task preferences, and sensing results to servers that will potentially disclose their daily routings, behavior patterns and even identities. With these concerns, the overall goal of this project is to address privacy leakage issues from different stages of mobile crowd sensing. Privacy-enhanced mobile crowd sensing will attract more participants and thus accelerate the maturity of smart health care, environment monitoring, traffic surveillance, social event observation, etc. In addition, this project will also serve as a training ground for educating future decision-makers and workforce on theory and tools. The PIs plan to develop effective and efficient privacy preservation schemes for different stages of mobile crowd sensing. It corresponds to three closely intertwined research thrusts. Thrust I explores protecting user's sensitive information, such as locations, sensing capabilities and task preferences, from the server, while still allowing it to optimally or approximately solve task allocation problems. Rather than highly computationally-intensive crypto-based techniques, privacy preservation schemes will be designed based on decomposition methods and distributed computing algorithms. Thrust II aims to provide user's location privacy in the stage of data collection. Since locations of users, who perform sensing over the same event within a certain geographic area, are highly correlated, it deteriorates user's privacy achieved individually. To address this issue, privacy preservation schemes will be developed by exploring collaborations among users. Game theories will be adopted to further analyze users' strategies and interactions. The objective of Thrust III is to protect users' sensing data privacy during the stage of data analysis. The research is featured by jointly considering the data imperfection that is caused by the limited sensing capabilities at mobile devices and even the misbehavior of lazy/malicious users. To achieve data privacy and service accuracy simultaneously, novel schemes will be developed combining efficient matrix completion methods and advanced crypto techniques.
包括智能手机和平板电脑在内的移动设备如今变得非常普遍。移动设备配备了从GPS到摄像头的各种传感器,再加上其所有者固有的移动性,能够获取周围环境的丰富信息。然而,移动人群传感的广泛采用在很大程度上受到隐私问题的阻碍。为了促进移动人群传感的每个阶段的功能,包括传感任务分配、传感数据收集和结果聚合,传感设备将其位置信息、传感能力、任务偏好和传感结果报告给服务器,这些服务器可能会披露其日常路由、行为模式甚至身份。考虑到这些问题,这个项目的总体目标是解决移动人群感知不同阶段的隐私泄露问题。增强隐私的移动人群感知将吸引更多的参与者,从而加速智能医疗、环境监测、交通监控、社会事件观察等领域的成熟。此外,该项目还将为未来的决策者和劳动力提供理论和工具方面的培训。计划为流动人群感应的不同阶段制定有效和高效的隐私保护方案。它对应于三个紧密交织在一起的研究重点。推力I探索保护用户的敏感信息,如位置、传感能力和任务偏好,不受服务器的影响,同时仍然允许它以最佳或近似的方式解决任务分配问题。隐私保护方案将基于分解方法和分布式计算算法来设计,而不是基于高度计算密集型的基于加密的技术。Thrust II旨在提供用户在数据收集阶段的位置隐私。由于在特定地理区域内对同一事件执行感知的用户的位置高度相关,因此它会恶化用户单独获得的隐私。为了解决这个问题,隐私保护方案将通过探索用户之间的合作来开发。博弈论将进一步分析用户的策略和互动。Thrust III的目标是在数据分析阶段保护用户的传感数据隐私。该研究的特点是综合考虑了由于移动设备的传感能力有限而导致的数据不完善,甚至是懒惰/恶意用户的不当行为。为了同时实现数据隐私和服务准确性,将开发结合高效矩阵补全方法和先进加密技术的新方案。
项目成果
期刊论文数量(11)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Motivating Human-Enabled Mobile Participation for Data Offloading
- DOI:10.1109/tmc.2017.2773087
- 发表时间:2018-07
- 期刊:
- 影响因子:7.9
- 作者:Xiaonan Zhang;Linke Guo;Ming Li;Yuguang Fang
- 通讯作者:Xiaonan Zhang;Linke Guo;Ming Li;Yuguang Fang
DPDA: A Differentially Private Double Auction Scheme for Mobile Crowd Sensing
- DOI:10.1109/cns.2018.8433135
- 发表时间:2018-05
- 期刊:
- 影响因子:0
- 作者:Wenqiang Jin;Ming Li;Linke Guo;Lei Yang
- 通讯作者:Wenqiang Jin;Ming Li;Linke Guo;Lei Yang
If You Do Not Care About It, Sell It: Trading Location Privacy in Mobile Crowd Sensing
- DOI:10.1109/infocom.2019.8737457
- 发表时间:2019-04
- 期刊:
- 影响因子:0
- 作者:Wenqiang Jin;Mingyan Xiao;Ming Li;Linke Guo
- 通讯作者:Wenqiang Jin;Mingyan Xiao;Ming Li;Linke Guo
Securing Task Allocation in Mobile Crowd Sensing: An Incentive Design Approach
- DOI:10.1109/cns.2019.8802697
- 发表时间:2019-06
- 期刊:
- 影响因子:0
- 作者:Mingyan Xiao;Ming Li;Linke Guo;M. Pan;Zhu Han;Pan Li
- 通讯作者:Mingyan Xiao;Ming Li;Linke Guo;M. Pan;Zhu Han;Pan Li
CREAM: Unauthorized Secondary User Detection in Fading Environments
- DOI:10.1109/mass.2018.00064
- 发表时间:2018-10
- 期刊:
- 影响因子:0
- 作者:Xiaonan Zhang;Pei Huang;Qi Jia;Linke Guo
- 通讯作者:Xiaonan Zhang;Pei Huang;Qi Jia;Linke Guo
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Linke Guo其他文献
FreeEM: Uncovering Parallel Memory EMR Covert Communication in Volatile Environments
FreeEM:揭示不稳定环境中的并行内存 EMR 隐蔽通信
- DOI:
10.1145/3643832.3661870 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Sihan Yu;Jingjing Fu;Chenxu Jiang;ChunChih Lin;Zhenkai Zhang;Long Cheng;Ming Li;Xiaonan Zhang;Linke Guo - 通讯作者:
Linke Guo
Extreme weather, IT investment, and corporate sustainability
极端天气、信息技术投资和企业可持续性
- DOI:
10.1057/s41599-025-05275-z - 发表时间:
2025-06-18 - 期刊:
- 影响因子:3.600
- 作者:
Peinan Ji;Linke Guo;Xiangbin Yan;Lianchao Yu - 通讯作者:
Lianchao Yu
Physiological and transcriptomic responses of the microalga Isochrysis galbana during exposure to Hg(II) stress
- DOI:
10.1007/s11274-025-04330-w - 发表时间:
2025-05-05 - 期刊:
- 影响因子:4.200
- 作者:
Linlin Zhang;Na Li;Xinfeng Xiao;Linke Guo;Wenfang Li;Yanjun Li;Fei Ling - 通讯作者:
Fei Ling
User-centric private matching for eHealth networks - A social perspective
以用户为中心的电子医疗网络私人匹配 - 社会视角
- DOI:
10.1109/glocom.2012.6503200 - 发表时间:
2012 - 期刊:
- 影响因子:0
- 作者:
Linke Guo;Xinxin Liu;Yuguang Fang;Xiaolin Li - 通讯作者:
Xiaolin Li
Linke Guo的其他文献
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{{ truncateString('Linke Guo', 18)}}的其他基金
Collaborative Research: SHF: Medium: Towards Harmonious Federated Intelligence in Heterogeneous Edge Computing via Data Migration
协作研究:SHF:中:通过数据迁移实现异构边缘计算中的和谐联邦智能
- 批准号:
2312616 - 财政年份:2023
- 资助金额:
$ 15万 - 项目类别:
Continuing Grant
Collaborative Research: CNS Core: Small: Scalable, Flexible, and Dependable Architecture Design for Heterogeneous Internet of Things
合作研究:CNS核心:小型:异构物联网的可扩展、灵活、可靠的架构设计
- 批准号:
2008049 - 财政年份:2020
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
CCSS: Collaborative Research: Towards Privacy-Preserving Mobile Crowd Sensing: A Multi-Stage Solution
CCSS:协作研究:迈向保护隐私的移动人群感知:多阶段解决方案
- 批准号:
1949639 - 财政年份:2019
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
EAGER: Malicious Behavior Detection in Hybrid Dynamic Spectrum Access
EAGER:混合动态频谱访问中的恶意行为检测
- 批准号:
1947065 - 财政年份:2019
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
SCH: INT: Collaborative Research: Crowd in Action: Human-Centric Privacy-Preserving Data Analytics for Environmental Public Health
SCH:INT:协作研究:人群在行动:以人为本的隐私保护环境公共卫生数据分析
- 批准号:
1949640 - 财政年份:2019
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
SCH: INT: Collaborative Research: Crowd in Action: Human-Centric Privacy-Preserving Data Analytics for Environmental Public Health
SCH:INT:协作研究:人群在行动:以人为本的隐私保护环境公共卫生数据分析
- 批准号:
1722731 - 财政年份:2017
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
EAGER: Malicious Behavior Detection in Hybrid Dynamic Spectrum Access
EAGER:混合动态频谱访问中的恶意行为检测
- 批准号:
1744261 - 财政年份:2017
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
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