TWC: TTP Option: Medium: Scalable Web Transparency: New Scientific Building Blocks, Tools, and Measurements to Tame the Data-Driven Web

TWC：TTP 选项：中：可扩展的网络透明度：驯服数据驱动网络的新科学构建模块、工具和测量

• 批准号: 1514437
• 负责人: Roxana Geambasu
• 金额: $ 158.9万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1514437&HistoricalAwards=false
• 关键词: TWC; TTP; Option; Medium; Scalable

With the advent of "big data," the Web has become a highly potent and opaque place which, left unchecked, can breed data misuse and unfair practices toward individuals. Today's Web services accumulate staggering amounts of personal data, such as emails, searches, and activity logs. They are mined for business value, retained for extended periods of time, and at times shared with third parties -- all without individuals' knowledge or explicit consent. Are these uses good or bad for individuals? Do they match a service's privacy policy? How long is data used after deletion? Who shares data with whom? Presently, there is little insight into these questions. This project creates a set of building blocks to track different types of individual data (e.g., keywords used in searches, previous sites visited) and measure multiple types of use (e.g., targeted advertising). These are used to develop robust and scalable tools for tracking data to uncover misuse.Our project seeks to increase the data-driven Web's transparency by developing both the tools and the scientific foundations for tracking the data's journey on the web. We make contributions on three fronts. First, we design a set of building blocks, highly reusable and scalable components that facilitate the building of a new generation of auditing tools to lift the curtain on how personal data is being used. Second, we build a set of robust and scalable transparency tools that instantiate those building blocks and enable users, journalists, and investigators to obtain visibility into Web services' data uses. We are actively seeking out deployments through collaborations with journalists and investigators. Third, we leverage these tools to run extensive measurement studies of various data-driven platforms, such as targeted advertising ecosystems, data brokers, and online price discrimination. These studies increase awareness, and help uncover examples of data mistreatment, which we hope will provide the grounds for an informed societal argument on the need for increased voluntary transparency on the Web.

随着“大数据”的出现，网络已经成为一个高度有效和不透明的地方，如果不加以控制，可能会滋生数据滥用和对个人的不公平做法。今天的Web服务积累了惊人数量的个人数据，如电子邮件、搜索和活动日志。它们被挖掘为商业价值，保留很长一段时间，有时与第三方共享-所有这些都没有个人的知识或明确同意。这些用途对个人来说是好还是坏？它们是否符合服务的隐私政策？数据删除后会使用多长时间？谁与谁共享数据？ 目前，对这些问题的了解还很少。 该项目创建了一组构建块来跟踪不同类型的个体数据（例如，在搜索中使用的关键字，先前访问的站点）并测量多种类型的使用（例如，定向广告）。 我们的项目旨在通过开发工具和科学基础来跟踪数据在网络上的旅程，从而提高数据驱动的Web的透明度。我们在三个方面作出贡献。 首先，我们设计了一套构建模块，高度可重用和可扩展的组件，以促进新一代审计工具的构建，从而揭开个人数据使用方式的序幕。 其次，我们构建了一组健壮且可扩展的透明工具，这些工具实例化了这些构建块，并使用户、记者和调查人员能够了解Web服务的数据使用情况。我们正在通过与记者和调查人员的合作积极寻求部署。 第三，我们利用这些工具对各种数据驱动的平台进行广泛的测量研究，例如有针对性的广告生态系统，数据经纪人和在线价格歧视。这些研究提高了人们的认识，并有助于发现数据滥用的例子，我们希望这将为一个明智的社会争论提供基础，即需要增加网络上的自愿透明度。