SaTC: Frontiers: Collaborative: Protecting Personal Data Flow on the Internet

SaTC：前沿：协作：保护互联网上的个人数据流

• 批准号: 1955227
• 负责人: David Choffnes
• 金额: $ 169.73万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1955227&HistoricalAwards=false
• 关键词: SaTC; Frontiers; Collaborative; Protecting; Personal

Personal data collection typically starts on user devices, with the data then shared with service providers and trackers, obtained by malicious actors, and/or used for surveillance. The services enabled by this data come at the expense of privacy, security, transparency, and fairness, for individuals and society as a whole. Increased public awareness has led to landmark legislation on data protection, such as the EU’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). Policymakers need to be further informed by technology, however, to formulate relevant and enforceable policies, and end-users still need tools to protect themselves. This project seeks to protect personal information, by improving the transparency and control of data flow on the Internet, using a multidisciplinary approach that combines methodologies from computer science (theory, network measurement, security) with policy and economics, and crosses multiple application domains (web, mobile, and Internet-of-Things). Conceptual frameworks are developed for personal information flow on the Internet, as well as systems for monitoring and mediation. Existing systems are improved for measuring the tracking and discrimination of personal information, and for explicitly controlling privacy-utility tradeoffs. To provide long-term privacy-by-design alternatives, the project pursues verifiable IoT architectures seeking to decentralize the advertising ecosystem and eliminate intermediaries. The project likewise leverages technology to inform policy specification and to provide tools to audit and enforce policies. The broader impacts of the project include: (1) informing policymakers, nonprofit advocates, and industry players through interactions with relevant stakeholders; (2) training next-generation graduate and undergraduate students jointly in technology and policy; and (3) broadening participation of women, underrepresented minorities, and community college students.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.

个人数据收集通常从用户设备开始，然后与服务提供商和跟踪器共享数据，由恶意行为者获取和/或用于监视，而这些数据启用的服务是以牺牲隐私、安全性、透明度和隐私为代价的。对于个人和整个社会而言，公众意识的提高导致了具有里程碑意义的数据保护立法，例如欧盟的《通用数据保护条例》（GDPR）和《加州消费者隐私法》（CCPA），政策制定者需要进一步了解。然而，制定相关且可执行的技术该项目旨在通过提高互联网数据流的透明度和控制，使用结合了计算机科学方法（理论、网络测量、安全）与政策和经济，并跨越多个应用领域（网络、移动和物联网）。为互联网上的个人信息流开发了概念框架，并对现有系统进行了改进。用于测量跟踪和歧视为了提供长期的隐私设计替代方案，该项目追求可验证的物联网架构，旨在分散广告生态系统并消除中介机构。该项目的更广泛影响包括：（1）通过与相关利益相关者的互动向政策制定者、非营利倡导者和行业参与者提供信息；（2）联合培训下一代研究生和本科生。和政策；以及(3) 扩大女性、代表性不足的少数族裔和社区学院学生的参与。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，认为值得支持。

项目成果

Understanding Dark Patterns in Home IoT Devices

了解家庭物联网设备中的深色图案

• DOI: 10.1145/3544548.3581432
• 发表时间: 2023-04-19
• 期刊: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
• 作者: M. Kowalczyk;Johanna T. Gunawan;D. Choffnes;Daniel J. Dubois;Woodrow Hartzog;Christo Wilson
• 通讯作者: Christo Wilson

Algorithms that "Don't See Color": Measuring Biases in Lookalike and Special Ad Audiences

“看不到颜色”的算法：测量相似和特殊广告受众的偏差

• DOI: 10.1145/3514094.3534135
• 发表时间: 2022-01
• 期刊: and Society
• 作者: Sapiezynski, Piotr;Ghosh, Avijit;Kaplan, Levi;Rieke, Aaron;Mislove, Alan
• 通讯作者: Mislove, Alan

Detecting consumer IoT devices through the lens of an ISP

通过 ISP 的视角检测消费者物联网设备

• DOI: 10.1145/3472305.3472885
• 发表时间: 2021-01
• 期刊: ANRW '21: Proceedings of the Applied Networking Research Workshop
• 作者: Saidi, Said Jawad;Mandalari, Anna Maria;Haddadi, Hamed;Dubois, Daniel J.;Choffnes, David;Smaragdakis, Georgios;Feldmann, Anja
• 通讯作者: Feldmann, Anja

Protected or Porous: A Comparative Analysis of Threat Detection Capability of IoT Safeguards

受保护还是有漏洞：物联网防护措施威胁检测能力的比较分析

• 发表时间: 2023-05
• 期刊: 2023 IEEE Symposium on Security and Privacy (SP
• 作者: Mandalari, Anna;Haddadi, Hamed;Dubois, Daniel J.;Choffnes, David
• 通讯作者: Choffnes, David

Measurement and analysis of implied identity in ad delivery optimization

广告投放优化中隐含身份的测量和分析

• DOI: 10.1145/3517745.3561450
• 发表时间: 2022-10
• 期刊: Proceedings of the 2022 ACM Internet Measurement Conference
• 作者: Kaplan, Levi;Gerzon, Nicole;Mislove, Alan;Sapiezynski, Piotr
• 通讯作者: Sapiezynski, Piotr