Collaborative Research: SaTC: CORE: Small: Supporting Privacy Negotiation Among Multiple Stakeholders in Smart Environments

协作研究:SaTC:核心:小型:支持智能环境中多个利益相关者之间的隐私谈判

基本信息

  • 批准号:
    2232656
  • 负责人:
  • 金额:
    $ 14.56万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard 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

Internet-of-Things (IoT) devices are increasingly used in shared spaces (e.g., homes, apartments, schools, hospitals, workplaces, and cities), turning these spaces into smart environments. Different stakeholders in these environments, including both direct users of smart devices and non-users such as visitors or bystanders, have unique privacy needs and expectations. Although prior research shows evidence of conflicts among stakeholders, there has been less investigation regarding how stakeholders resolve such conflicts and negotiate their privacy options. This interdisciplinary project is investigating different stakeholders’ privacy negotiation behaviors in smart environments by designing, developing, and deploying an interactive system to collect people’s real-world privacy negotiation behaviors. The project is contributing solutions that help people manage and negotiate their privacy in various smart environments, especially when their privacy needs conflict with others’. The results will also inform privacy negotiations within other emerging technologies (e.g., virtual reality and the metaverse).This project moves beyond the lab setting to investigate and support stakeholders’ privacy negotiation behaviors in real-world smart environments. To do this, the project team is identifying contextual factors that lead to privacy concerns across multiple stakeholder groups and complex smart environments through the lens of privacy as “contextual integrity”. It is capturing stakeholders’ privacy negotiation behaviors in the real world by iteratively designing and implementing a tool that collects data on smart environmental contexts and privacy negotiation behaviors in real-world smart environments. Finally, it is developing a data-driven approach to support privacy negotiations in the real-world and evaluating its long-term impact on different stakeholder groups through field studies. The team is facilitating the future extension of this work to other new technologies by publicly sharing the anonymized dataset collected using the developed system, features of the project’s machine learning models, and a working prototype of the system.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.
物联网 (IoT) 设备越来越多地用于共享空间(例如家庭、公寓、学校、医院、工作场所和城市),将这些空间转变为智能环境,包括这些环境中的不同利益相关者,包括直接用户。智能设备和非用户(例如访客或旁观者)具有独特的隐私需求和期望,尽管先前的研究表明利益相关者之间存在冲突,但关于利益相关者如何解决此类冲突并协商其隐私选择的调查较少。调查不同利益相关者的隐私谈判通过设计、开发和部署一个交互式系统来收集人们在现实世界中的隐私协商行为,该项目正在提供解决方案,帮助人们在各种智能环境中管理和协商他们的隐私,特别是当他们的隐私需求与其他人发生冲突时。结果还将为其他新兴技术(例如虚拟现实和元宇宙)中的隐私谈判提供信息。该项目超越了实验室环境,调查和支持利益相关者在现实世界智能环境中的隐私谈判行为。项目团队正在识别导致隐私的背景因素它通过迭代设计和实施收集智能环境背景和隐私谈判行为数据的工具来捕获现实世界中利益相关者的隐私谈判行为。最后,它正在开发一种数据驱动的方法来支持现实世界中的隐私谈判,并通过实地研究评估其对不同利益相关者群体的长期影响。通过公开分享来研究其他新技术使用开发的系统收集的匿名数据集、项目机器学习模型的特征以及系统的工作原型。该奖项反映了 NSF 的法定使命,并通过使用基金会的智力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

期刊论文数量(0)
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会议论文数量(0)
专利数量(0)

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Jessica Vitak其他文献

The Platformization of the Classroom: Teachers as Surveillant Consumers
课堂的平台化:教师作为监视消费者
  • DOI:
    10.24908/ss.v17i1/2.12926
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    2
  • 作者:
    Priya C. Kumar;Jessica Vitak;M. Chetty;Tamara L. Clegg
  • 通讯作者:
    Tamara L. Clegg
Users and nonusers: interactions between levels of adoption and social capital
用户和非用户:采用水平和社会资本之间的相互作用
Happiness and Fear
幸福与恐惧
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    P. Wisniewski;Karla A. Badillo;Zahra Ashktorab;Jessica Vitak
  • 通讯作者:
    Jessica Vitak
Balancing Audience and Privacy Tensions on Social Network Sites: Strategies of Highly Engaged Users
平衡社交网站上的受众和隐私紧张:高度参与的用户的策略
  • DOI:
  • 发表时间:
    2015
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jessica Vitak;Stacy Blasiola;S. Patil;E. Litt
  • 通讯作者:
    E. Litt
Norm evolution and violation on Facebook
Facebook 上的规范演变与违反
  • DOI:
    10.1177/1461444811412712
  • 发表时间:
    2012
  • 期刊:
  • 影响因子:
    5
  • 作者:
    Caitlin McLaughlin;Jessica Vitak
  • 通讯作者:
    Jessica Vitak

Jessica Vitak的其他文献

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{{ truncateString('Jessica Vitak', 18)}}的其他基金

SaTC: EDU: Collaborative: Connecting Contexts: Building Foundational Digital Privacy and Security Skills for Elementary School Children, Teachers, and Parents
SaTC:EDU:协作:连接环境:为小学生、教师和家长建立基本的数字隐私和安全技能
  • 批准号:
    1951688
  • 财政年份:
    2020
  • 资助金额:
    $ 14.56万
  • 项目类别:
    Standard Grant
WORKSHOP: Doctoral Consortium at the 2020 Conference on Computer Supported Cooperative Work and Social Computing
研讨会:2020 年计算机支持的协作工作和社会计算会议上的博士联盟
  • 批准号:
    2039317
  • 财政年份:
    2020
  • 资助金额:
    $ 14.56万
  • 项目类别:
    Standard Grant
EAGER: Collaborative: Mapping Privacy and Surveillance Dynamics in Emerging Mobile Ecosystems: Practices and Contexts in the Netherlands and US
EAGER:协作:绘制新兴移动生态系统中的隐私和监控动态:荷兰和美国的实践和背景
  • 批准号:
    1640640
  • 财政年份:
    2016
  • 资助金额:
    $ 14.56万
  • 项目类别:
    Standard Grant

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相似海外基金

Collaborative Research: SaTC: CORE: Medium: Differentially Private SQL with flexible privacy modeling, machine-checked system design, and accuracy optimization
协作研究:SaTC:核心:中:具有灵活隐私建模、机器检查系统设计和准确性优化的差异化私有 SQL
  • 批准号:
    2317232
  • 财政年份:
    2024
  • 资助金额:
    $ 14.56万
  • 项目类别:
    Continuing Grant
Collaborative Research: SaTC: CORE: Medium: Using Intelligent Conversational Agents to Empower Adolescents to be Resilient Against Cybergrooming
合作研究:SaTC:核心:中:使用智能会话代理使青少年能够抵御网络诱骗
  • 批准号:
    2330940
  • 财政年份:
    2024
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    $ 14.56万
  • 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:
    $ 14.56万
  • 项目类别:
    Continuing Grant
Collaborative Research: SaTC: CORE: Medium: Differentially Private SQL with flexible privacy modeling, machine-checked system design, and accuracy optimization
协作研究:SaTC:核心:中:具有灵活隐私建模、机器检查系统设计和准确性优化的差异化私有 SQL
  • 批准号:
    2317233
  • 财政年份:
    2024
  • 资助金额:
    $ 14.56万
  • 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:
    2338302
  • 财政年份:
    2024
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