个人数据库:个人数据流的控制点

Min Y. Mun, Shuai Hao, Nilesh Mishra, Katie Shilton, J. Burke, D. Estrin, Mark H. Hansen, R. Govindan
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引用次数: 153

摘要

移动电话的日益普及为个人环境感知创造了许多机会,并将导致包含位置、运动、图像、文本注释甚至健康数据的个人敏感信息的庞大数据库。在现有的系统架构中,用户将他们的原始(未处理或过滤的)数据流直接上传到内容服务提供商,一旦他们“选择加入”,就几乎无法控制他们的数据。我们提出了个人数据库(pdv),这是一种个人保留其数据所有权的隐私架构。数据在与内容服务提供商共享之前通常会经过过滤,用户或数据托管服务可以参与制定受控的数据共享决策。引入PDV为用户提供了对数据的灵活和细粒度访问控制。为了减轻用户负担并提高可用性,我们探索了管理数据策略的三种机制:粒度ACL、跟踪审计和规则推荐。我们已经实现了一个概念验证PDV,并使用从两个个人参与式传感应用中收集的真实数据痕迹对其进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Personal data vaults: a locus of control for personal data streams
The increasing ubiquity of the mobile phone is creating many opportunities for personal context sensing, and will result in massive databases of individuals' sensitive information incorporating locations, movements, images, text annotations, and even health data. In existing system architectures, users upload their raw (unprocessed or filtered) data streams directly to content-service providers and have little control over their data once they "opt-in". We present Personal Data Vaults (PDVs), a privacy architecture in which individuals retain ownership of their data. Data are routinely filtered before being shared with content-service providers, and users or data custodian services can participate in making controlled data-sharing decisions. Introducing a PDV gives users flexible and granular access control over data. To reduce the burden on users and improve usability, we explore three mechanisms for managing data policies: Granular ACL, Trace-audit and Rule Recommender. We have implemented a proof-of-concept PDV and evaluated it using real data traces collected from two personal participatory sensing applications.
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