Understanding and minimizing identity exposure in ubiquitous computing environments

Feng Zhu, S. Carpenter, Ajinkya Kulkarni, Chockalingam Chidambaram, Shruti Pathak
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引用次数: 10

Abstract

Various miniaturized computing devices that store our identities are emerging rapidly. They allow our identity information to be easily exposed and accessed via wireless networks. When identity information is associated with our personal and context information that is gathered by ubiquitous computing devices, personal privacy might be unprecedentedly sacrificed. People, however, have different privacy protection skills, awareness, and privacy preferences. Individuals can be uniquely identified on the basis of only a few identity elements used in combination. To the best of our knowledge, this is the first study to understand the following issues and their relations: a) what identity elements people think are important; b) what actions people claim to take to protect their identities and privacy; c) privacy concerns; d) how people expose their identities in ubiquitous computing environments; and e) how our rational identity exposure model can help to minimize identity exposure. We build a simulated ubiquitous computing shopping system, called InfoSource. It consists of two applications and our rational identity exposure model. We present our experiments and statistical analysis results. Our data show that exposure decisions depend on participants' attitudes about maintaining privacy, but they do not depend on participants' concerns and claimed actions related to identity exposure. Our RationalExposure model helped participants to minimize unnecessary exposures.
理解和最小化无处不在的计算环境中的身份暴露
存储我们身份的各种小型计算设备正在迅速出现。它们让我们的身份信息很容易通过无线网络暴露和访问。当身份信息与无处不在的计算设备收集的个人和上下文信息相关联时,个人隐私可能会受到前所未有的牺牲。然而,人们有不同的隐私保护技能、意识和隐私偏好。只要组合使用几个标识元素,就可以唯一地标识个人。据我们所知,这是第一个了解以下问题及其关系的研究:a)人们认为哪些身份要素是重要的;B)人们声称采取了哪些行动来保护他们的身份和隐私;C)隐私问题;D)人们如何在无处不在的计算环境中暴露自己的身份;e)我们的理性身份暴露模型如何帮助最小化身份暴露。我们建立了一个模拟的无处不在的计算购物系统,叫做InfoSource。它由两个应用程序和我们的理性身份暴露模型组成。给出了实验结果和统计分析结果。我们的数据表明,暴露决策取决于参与者对维护隐私的态度,但不取决于参与者对身份暴露的关注和声称的行动。我们的RationalExposure模型帮助参与者减少不必要的暴露。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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