Privacy-enhanced personalization for online learning

在线学习的隐私增强个性化

• 批准号: 41799-2007
• 负责人: Greer, Jim
• 金额: $ 2.08万
• 依托单位: University of Saskatchewan
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2008
• 资助国家: 加拿大
• 起止时间: 2008-01-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=390391
• 关键词: Privacy; enhanced; personalization; online; learning

Computer systems that personalize their actions in reaction to personal preferences or requirements of human users do so by building profiles of the users. These profiles are based on knowledge gained either from analysis of user interactions with the system or from outside data sources. In either circumstance, there is a potential threat to user privacy. Research by me and others has been devoted to providing personalization support while preserving user privacy. One key approach has been to separate the system's knowledge of the personal identity of the user from the behaviour that is being monitored. This can be achieved by providing a pseudonym for the user and associating behaviour information with the pseudonymous identity. But pseudonymity introduces both social and technical challenges for personalization systems.

根据人类用户的个人偏好或要求来个性化其行为的计算机系统是通过构建用户的配置文件来实现的。这些配置文件基于从用户与系统交互的分析或从外部数据源获得的知识。无论哪种情况，都对用户隐私存在潜在威胁。我和其他人的研究致力于提供个性化支持，同时保护用户隐私。一种关键方法是将系统对用户个人身份的了解与正在监控的行为分开。这可以通过为用户提供假名并将行为信息与假名身份相关联来实现。但假名给个性化系统带来了社会和技术挑战。