CAREER: Sensible Privacy: Pragmatic Privacy Controls in an Era of Sensor-Enabled Computing

职业：敏感隐私：传感器计算时代的实用隐私控制

• 批准号: 1252697
• 负责人: Apu Kapadia
• 金额: $ 55.09万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1252697&HistoricalAwards=false
• 关键词: CAREER; Sensible; Privacy; Pragmatic; Controls

Social networking and sensor-rich devices such as smartphones are becoming increasingly pervasive in today's society. People can share information concerning their location, activity, fitness, and health with their friends and family while benefiting from applications that leverage such information. Yet, users already find managing their privacy to be challenging, and the complexity involved in doing so is bound to increase. Usable techniques are required to enable people to effectively manage the dissemination of their private information as sensed by their mobile devices and sensors in their environment. This project explores `sensible' privacy controls and feedback mechanisms that allow people (or automated mechanisms acting on their behalf) to respond to unanticipated patterns and actual uses of their information in a way that is usable and intuitive. This approach has two advantages: 1) people need only care about the subset of data and usage scenarios that have the potential to violate their privacy, thus reducing the amount of data to which they must regulate access; and 2) people make better decisions concerning such access when these decisions are made in a context where they know how their data is being used. Sensible privacy mechanisms can have a profound and positive societal impact by not only helping people control their privacy, but also potentially increasing their participation in sensor-enabled computing because of this added control. This project firmly integrates education into the research through research experiences for underrepresented groups and the development of course modules on privacy at the undergraduate and graduate levels.

社交网络和智能手机等传感器丰富的设备在当今社会中变得越来越普遍。人们可以与他们的朋友和家人分享有关他们的位置，活动，健身和健康的信息，同时受益于利用这些信息的应用程序。然而，用户已经发现管理他们的隐私是一项挑战，而且这样做的复杂性肯定会增加。需要可用的技术来使人们能够有效地管理由他们的环境中的他们的移动的设备和传感器感测到的他们的私人信息的传播。该项目探讨了“明智的”隐私控制和反馈机制，使人们（或代表他们行事的自动机制）能够以可用和直观的方式对其信息的意外模式和实际使用作出反应。 这种方法有两个优点：1）人们只需要关心有可能侵犯其隐私的数据子集和使用场景，从而减少了他们必须管理访问的数据量; 2）当人们在知道他们的数据如何被使用的情况下做出这些决策时，他们会做出更好的关于这种访问的决策。 合理的隐私机制不仅可以帮助人们控制自己的隐私，而且还可以通过这种额外的控制来增加他们对传感器计算的参与，从而产生深远而积极的社会影响。该项目通过为代表性不足的群体提供研究经验，并在本科生和研究生一级开发关于隐私的课程模块，将教育牢固地融入研究。