EAGER: Understanding and Categorizing Metadata

通信元数据是提供服务所必需的。但这样的元数据会泄露有关用户意图和行为的信息。例如，通过计时，人们可以确定Twitter账户是否是机器人，而通过分组长度，可以确定加密的互联网协议语音(VoIP)呼叫中使用的是什么语言。因此，保护用户的隐私和安全是复杂的。通过检查多组不同的元数据用法，这位热心人试图开发一种对元数据所揭示的信息类型的分类。这项工作的应用应导致制定对用户隐私和安全的更好的技术和政策保护。这项拟议研究的主要贡献是对元数据应用的用途类型进行了分类。元数据的使用有许多用途(数据是如何收集的，它是否与其他数据聚合，等等)；这种分类将侧重于开发通过元数据捕获和使用揭示的干净类型的信息。这种对元数据使用的分类将有几个重要的应用。描述通过使用元数据获得的不同类型的知识(例如，关于设备的信息、关于用户的信息)，将简化对用户隐私和安全的更好的技术保护，使其免受此类攻击。此外，通过对元数据的不同使用方式进行分类，可以更容易地了解哪些使用是隐私侵犯，哪些不是，从而围绕元数据使用制定更多隐私保护政策。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Communications metadata is necessary for the delivery of services. But such metadata leaks information about user intent and behavior. Through timing, for example, one can determine whether a Twitter account is a bot, while through packet length, what language is being spoken in an encrypted Voice Over Internet Protocol (VoIP) call. Thus, protecting a user's privacy and security is complicated. By examining multiple different sets of metadata usage, this EAGER seeks to develop a categorization of the types of information that metadata reveals. Applications of the work should lead to the development of better technical and policy protections of user privacy and security. The main contribution of this proposed research is a categorization of the types of uses to which metadata is applied. There are many uses in metadata usage (how is the data collected, is it aggregated with other data, etc.); this categorization will focus on developing clean types of information revealed through metadata capture and use. Such a categorization of metadata usage will have several important applications. Delineating different types of knowledge gained through the use of metadata (e.g., information about the device, information about the user), will simplify providing better technical protections for user privacy and security against such attacks. Furthermore, by categorizing the different ways metadata is used, it will be possible to more easily understand which usages are privacy invasive and which are not, and thus to develop more privacy-protective policies surrounding metadata usage.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.