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

随着诸如智能电话之类的传感器丰富的移动的设备的出现，越来越多的人正在与他们的社交网络的成员共享个人“上下文”信息，如位置、活动和健康/健身信息。 为了增强共享这些信息的人的隐私，大量的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。本研究通过解决“谁在访问我的信息，以及在多大程度上访问我的信息？”".为用户提供一个准确的感觉，他们的“曝光”，将使他们能够更好地控制他们的上下文信息是如何共享，并将有助于减轻新兴的隐私risks.This研究进步的最先进的隐私的概念正式化的安全意识的研究，并通过调查指标，可用于量化一个人？的暴露，开发可用的反馈模型和可视化，利用这些指标来传达暴露，并为已建立的策略架构创建暴露控制扩展，以帮助用户控制暴露并随着时间的推移完善其数据共享策略。 因此，拟议的研究将允许普通人主动控制在线共享的个人信息量，并将减少越来越多地使用社交网络应用程序共享个人上下文信息的大量用户的隐私风险。

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.