TC: Small: Collaborative Research: Improved Privacy though Exposure Control

随着智能手机等传感器丰富的移动设备的出现，越来越多的人开始与他们的社交网络成员分享个人“上下文”信息，如位置、活动和健康/健身信息。为了加强共享此类信息的人的隐私，大量研究集中在用户指定谁应该被授权访问他们的信息的方法上。这项研究通过解决“谁在访问我的信息，访问到什么程度？”这一相关问题，提高了终端用户的隐私。向用户提供他们“暴露”的准确感觉，将使他们能够更好地控制他们的上下文信息如何被共享，并有助于减轻新出现的隐私风险。这项研究通过形式化暴露意识研究的概念，以及通过调查可用于量化个人的指标，推动了隐私领域的最新发展。开发可用的反馈模型和可视化，利用这些指标来传达曝光，并为已建立的策略体系结构创建曝光控制扩展，以帮助用户控制曝光并随着时间的推移改进他们的数据共享策略。因此，拟议中的研究将允许普通人主动控制在线共享的个人信息的数量，并将减少大量用户的隐私风险，这些用户越来越多地使用社交网络应用程序来共享个人背景信息。

With the advent of sensor-rich mobile devices such as smartphones, an increasing number of people are sharing personal "contextual" information like location, activity, and health/fitness information with members of their social network. To enhance privacy for people sharing such information, a large body of research has focused on ways for users to specify who should be authorized to access their information. This research improves end-user privacy by addressing the related question of "Who is accessing my information and to what extent?". Providing users with an accurate sense of their "exposure" will enable them to better control how their contextual information is shared and will help mitigate emerging privacy risks.This research advances the state of the art in privacy by formalizing the notion of exposure-awareness research, and by investigating metrics that can be used to quantify a person?s exposure, developing usable feedback models and visualizations that leverage these metrics to convey exposure, and creating exposure control extensions to established policy architectures to help users control exposure and refine their data sharing policies over time. The proposed research will thus allow ordinary people to proactively rein in the amount of personal information shared online, and will reduce the privacy risks for the large population of users who are increasingly using social-networking applications to share personal contextual information.