PrivacyCheck v3: Empowering Users with Higher-Level Understanding of Privacy Policies

WSDM'22: PROCEEDINGS OF THE FIFTEENTH ACM INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING(2022)

引用 10|浏览0
暂无评分
摘要
ABSTRACTOnline privacy policies are lengthy and hard to read, yet are profoundly important as they communicate the practices of an organization pertaining to user data privacy. Privacy Enhancing Technologies, or PETs, seek to inform users by summarizing these privacy policies. Efforts in the research and development of such PETs, however, have largely been limited to tools that recap the policy or visualize it. We present the next generation of our research and publicly available tool, PrivacyCheck v3, that utilizes machine learning to inform and empower users with respect to privacy policies. PrivacyCheck v3 adds capabilities that are commonly absent from similar PETs on the web. In particular, it adds the ability to (1) find the competitors of an organization with Alexa traffic analysis and compare policies across them, (2) follow privacy policies to which the user has agreed and notify the user when policies change, (3) track policies over time and report how often policies change and their trends, (4) automatically find privacy policies in domains, and (5) provide a bird's-eye view of privacy policies. The new features of PrivacyCheck not only inform users about details of privacy policies, but also empower them to understand privacy policies at a higher level, make informed decisions, and even select competitors with better privacy policies.
更多
查看译文
关键词
privacy policy, privacy enhancing technologies, usable privacy, PrivacyCheck
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要