de Montjoye Yves-Alexandre, Shmueli Erez, Wang Samuel S, Pentland Alex Sandy
Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
DIG/CSAIL, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
PLoS One. 2014 Jul 9;9(7):e98790. doi: 10.1371/journal.pone.0098790. eCollection 2014.
The rise of smartphones and web services made possible the large-scale collection of personal metadata. Information about individuals' location, phone call logs, or web-searches, is collected and used intensively by organizations and big data researchers. Metadata has however yet to realize its full potential. Privacy and legal concerns, as well as the lack of technical solutions for personal metadata management is preventing metadata from being shared and reconciled under the control of the individual. This lack of access and control is furthermore fueling growing concerns, as it prevents individuals from understanding and managing the risks associated with the collection and use of their data. Our contribution is two-fold: (1) we describe openPDS, a personal metadata management framework that allows individuals to collect, store, and give fine-grained access to their metadata to third parties. It has been implemented in two field studies; (2) we introduce and analyze SafeAnswers, a new and practical way of protecting the privacy of metadata at an individual level. SafeAnswers turns a hard anonymization problem into a more tractable security one. It allows services to ask questions whose answers are calculated against the metadata instead of trying to anonymize individuals' metadata. The dimensionality of the data shared with the services is reduced from high-dimensional metadata to low-dimensional answers that are less likely to be re-identifiable and to contain sensitive information. These answers can then be directly shared individually or in aggregate. openPDS and SafeAnswers provide a new way of dynamically protecting personal metadata, thereby supporting the creation of smart data-driven services and data science research.
智能手机和网络服务的兴起使得大规模收集个人元数据成为可能。有关个人位置、通话记录或网络搜索的信息被组织和大数据研究人员大量收集和使用。然而，元数据尚未充分发挥其潜力。隐私和法律问题，以及缺乏个人元数据管理的技术解决方案，阻碍了元数据在个人控制下的共享和协调。这种对元数据的访问和控制权的缺失进一步加剧了人们日益增长的担忧，因为它使个人无法理解和管理与其数据收集和使用相关的风险。我们的贡献有两方面：（1）我们描述了openPDS，这是一个个人元数据管理框架，允许个人收集、存储其元数据，并向第三方提供细粒度的访问权限。它已在两项实地研究中得到实施；（2）我们引入并分析了SafeAnswers，这是一种在个人层面保护元数据隐私的全新实用方法。SafeAnswers将一个棘手的匿名化问题转化为一个更易于处理的安全问题。它允许服务提出问题，并根据元数据计算答案，而不是试图对个人元数据进行匿名化处理。与服务共享的数据维度从高维元数据降低到低维答案，这些答案不太可能被重新识别，也不太可能包含敏感信息。然后，这些答案可以直接单独或汇总共享。openPDS和SafeAnswers提供了一种动态保护个人元数据的新方法，从而支持创建智能数据驱动的服务和数据科学研究。
