CAREER: Privacy Analytics for Users in a Big Data World

越来越多的关于用户的数据被收集，越来越复杂的分析被应用于这些数据的各种目的。隐私分析是最终用户应用于其数据的机器学习和数据挖掘算法，目的是帮助他们管理私人信息和自我表现。这项研究开发了隐私分析，帮助用户回答关于他们在线角色的三个相互关联的问题(1)用户认为哪些数据是敏感的，在什么情况下应该分享这些数据？(2)数据说明了用户的哪些信息；(3)谁知道是什么？这些隐私分析引入了一种新颖的反向数据挖掘问题，即用户分析他们的数据以估计将这些数据合并到更大的数据集时将产生的结论。该项目为定量和自动化方法设计了新的算法，以检测已定性观察到的与隐私相关的现象。这些算法支持可用的隐私增强技术的发展，并将为用户提供在复杂数据环境中处理和管理数据的工具。这些工具将让用户了解他们的数据是如何被使用的。这些分析还将有助于回答对隐私法和政策发展至关重要的问题。这项工作涉及大约25名本科生的研究活动，使他们接触到研究方法和隐私问题。该项目还开发了新颖的教育材料，包括为安全和教育工具的跨学科硕士课程提供的课程，供公众使用，以弥合数字鸿沟。

Increasing amounts of data are being collected about users, and increasingly sophisticated analytics are being applied to this data for various purposes. Privacy analytics are machine learning and data mining algorithms applied by end-users to their data for the purpose of helping them manage both private information and their self-presentation. This research develops privacy analytics that help users answer three interconnected questions about their online persona (1) What data does the user consider sensitive, and in what contexts should one share it?; (2) What does the data say about the user; and (3) Who knows what? These privacy analytics introduce a novel, inverse data mining problem where users analyze their data to estimate the conclusions the data will produce when incorporated into larger data sets. This project designs new algorithms for quantitative and automated methods to detect privacy-related phenomena that have been observed qualitatively. These algorithms support the development of usable privacy enhancing technologies and will give users tools to cope with and manage their data in a complicated data environment. These tools will provide awareness to users about how their data is being used. These analytics will also help answer questions critical to the development of privacy law and policy.This work involves approximately twenty-five undergraduates in research activities, exposing them to research methods and privacy issues. This project also develops novel educational materials including course offerings for an interdisciplinary master's program in security and educational tools for use by the general public to bridge the digital divide.