Quantification of perceived location privacy, and its relationship to privacy behaviour

隐私是信息和通信技术日益重要的话题。从用户的在线活动和移动设备使用中收集大量数据，并将其汇总形成可能影响用户隐私的信息。尽管存在控制对这类信息的访问的机制，但普通用户几乎不可能理解和控制可以从收集的数据中提取的信息。在这种情况下，位置信息尤其值得关注，因为从看似匿名的位置数据可以推断出大量信息。用户在使用基于位置的系统时具有的隐私偏好通常可以在两个水平上测量：要么用户在特定情况下共享他们的位置，要么他们不共享。然而，用户的实际隐私偏好可能比这更细粒度。本研究项目的目标是(1)理解和量化这些偏好，(2)了解它们与公开分享行为的关系，(3)通过正式的建模使这些知识变得可用。第一个目标是通过量化赋值的方法评估细粒度的隐私偏好。第二个目标是通过实证研究这种量化的位置隐私评估如何反映在实际的隐私行为中，同时考虑到用户对位置共享的知识和意识。第三个目标是通过调整现有的行为模式，使移动环境中与隐私有关的行为正式化，从而实现第三个目标。

Privacy is an increasingly important topic for information and communication technologies. Massive amounts of data are collected from the users' online activities and mobile device usage, and aggregated to form information which can affect a user's privacy. Although mechanisms exist to control access to such information, it is mostly impossible for a common user to understand and control the information which can be extracted from collected data. Location information is of particular concern in this context, as from seemingly anonymous location data vast amounts of information can be inferred.Privacy preferences that users have when using location-based systems can typically be measured on a dichotomous level: either the users share their location in a certain situation or they do not. However, the users' actual privacy preferences are likely more fine-grained than this. It is the goal of this research project to (1) understand and quantify such preferences, (2) to understand how they relate to overt sharing behavior, and (3) to make this knowledge accessible through formal modelling. The first goal is reached by assessing fine-grained privacy preferences by a method of quantified value assignment. The second goal is reached by empirically studying how this quantified location privacy valuation is reflected in actual privacy behavior, taking the users' knowledge and awareness of location sharing into account. The third goal is reached by adapting existing behavioural models to formalize privacy-related behaviour in a mobile context.