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，越来越多的人正在与他们的社交网络成员分享个人“情境”信息，如位置、活动和健康/健身信息。为了增强共享此类信息的人的隐私，大量研究集中在让用户指定谁应该被授权访问他们的信息的方法。这项研究通过解决“谁在访问我的信息以及在多大程度上访问我的信息？”的相关问题来改善最终用户的隐私。为用户提供准确的曝光感觉将使他们能够更好地控制如何共享他们的上下文信息，并将有助于缓解新出现的隐私风险。这项研究通过将曝光意识研究的概念正式化，通过调查可用于量化个人的指标-S曝光，开发可用的反馈模型和可视化来利用这些指标来传达曝光，并创建曝光控制扩展到已建立的策略架构，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，从而推动了隐私领域的最新发展。因此，这项拟议的研究将使普通人能够主动控制在线共享的个人信息量，并将降低越来越多使用社交网络应用程序共享个人背景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.