标题： 移动电话数据在发展中的隐私-效用权衡映射 显示英文标题

标题： Mapping the Privacy-Utility Tradeoff in Mobile Phone Data for Development

摘要： 当今的数据时代具有很高的潜力，可以提升我们在发展和人道主义行动领域追求和监测进展的方式。 我们研究大规模行为数据中数据效用与隐私风险之间的关系，重点关注手机元数据作为典型领域。 为了衡量效用，我们调查了专家在不同空间和时间粒度级别下对手机元数据价值的看法。 为了衡量隐私，我们提出了一种形式化且直观的重新识别风险度量$\unicode{x2014}$信息比率$\unicode{x2014}$并在每个粒度级别上计算它。 我们的结果证实了数据效用与重新识别性之间存在明显的权衡，其中最有价值的数据集也最容易被重新识别。 当数据指定到邮编和小时级别时，仅需了解一个人数据的7%，即可完成重新识别并检索剩余的93%。 相比之下，在最有价值的数据集中，指定到市和每日级别时，平均需要了解一个人数据的51%，即31个数据点，才能检索剩余的49%。 总体而言，我们的发现表明，数据粗化会直接降低其价值，并强调需要将数据粗化与提供可调整的责任和安全程度的数据共享模型结合使用，而不是作为独立机制。 显示英文摘要

摘要： Today's age of data holds high potential to enhance the way we pursue and monitor progress in the fields of development and humanitarian action. We study the relation between data utility and privacy risk in large-scale behavioral data, focusing on mobile phone metadata as paradigmatic domain. To measure utility, we survey experts about the value of mobile phone metadata at various spatial and temporal granularity levels. To measure privacy, we propose a formal and intuitive measure of reidentification risk$\unicode{x2014}$the information ratio$\unicode{x2014}$and compute it at each granularity level. Our results confirm the existence of a stark tradeoff between data utility and reidentifiability, where the most valuable datasets are also most prone to reidentification. When data is specified at ZIP-code and hourly levels, outside knowledge of only 7% of a person's data suffices for reidentification and retrieval of the remaining 93%. In contrast, in the least valuable dataset, specified at municipality and daily levels, reidentification requires on average outside knowledge of 51%, or 31 data points, of a person's data to retrieve the remaining 49%. Overall, our findings show that coarsening data directly erodes its value, and highlight the need for using data-coarsening, not as stand-alone mechanism, but in combination with data-sharing models that provide adjustable degrees of accountability and security.