ABSTRACT

Despite several high-profile data breaches and business models that commercialize user data, participation in social media networks continues to require users to trust corporations to safeguard their personal data. Since these data increasingly contain geographic references that allude to individuals’ locations and movements, the need for new approaches to geoprivacy and data sovereignty has grown. We develop a geoprivacy framework that couples two emerging technologies – decentralized data storage and discrete global grid systems – to facilitate fine-grained user control over the ownership of, access to and map-based representation of their data. The framework is illustrated with a dynamic k-anonymity model that links the geographic precision of shared data to social trust within in a social network. In this framework, users’ spatio-temporal data are shared through a decentralized system and are represented on a discrete global grid data model at spatial resolutions that correspond to varying degrees of trust between individuals who are exchanging information. Our framework has several advantages over centralized geoprivacy approaches, namely trust in a third-party entity is not required and geoprivacy is dynamic and context-dependent with users maintaining autonomy. As the distributed web begins to emerge, so too can the next generation of geographic information sharing tools.

摘要

尽管发生了几起引人注目的数据泄露事件和将用户数据商业化的商业模式，但参与社交媒体网络仍然需要用户信任公司来保护他们的个人数据。由于这些数据越来越多地包含暗示个人位置和移动的地理参考，因此对地理隐私和数据主权的新方法的需求也在增长。我们开发了一个地理隐私框架，该框架结合了两种新兴技术——分散数据存储和离散全球网格系统——以促进用户对其数据的所有权、访问和基于地图的表示的细粒度控制。该框架用动态 k-匿名模型进行说明，该模型将共享数据的地理精度与社交网络中的社会信任联系起来。在这个框架中，用户的时空数据通过分散系统共享，并以空间分辨率表示在离散的全球网格数据模型上，对应于交换信息的个人之间不同程度的信任。与集中式地理隐私方法相比，我们的框架有几个优点，即不需要对第三方实体的信任，并且地理隐私是动态的且依赖于用户保持自主权的上下文。随着分布式网络的出现，下一代地理信息共享工具也将出现。与集中式地理隐私方法相比，我们的框架有几个优点，即不需要对第三方实体的信任，并且地理隐私是动态的且依赖于用户保持自主权的上下文。随着分布式网络的出现，下一代地理信息共享工具也将出现。与集中式地理隐私方法相比，我们的框架有几个优点，即不需要对第三方实体的信任，并且地理隐私是动态的且依赖于用户保持自主权的上下文。随着分布式网络的出现，下一代地理信息共享工具也将出现。