TWC: Medium: Understanding and Illuminating Non-Public Data Flows

我们的生活被一个持续不断的数据网络所包围，这些数据被一个由看不见的程序组成的全球网络所采集，这些程序收集、合并、组合和合并它们所能获得的每一点数据。这些项目和公司在公众视野之外运作，在公众不知情的情况下收集和交换数据以获取利润。这是一个复杂的生态系统，数据的原始收集者可能不知道最终用途，数据的用户可能不知道原始来源。该项目试图通过一系列实验，通过选择性地添加或检索信息来测量和干扰看不见的数据池，从而阐明这个生态系统。此外，该项目还侧重于创建陷阱和触发器，以及未来数据提供商可能使用的人工数据，从而发现新的数据收集和使用。最后，仅仅研究这一现象是不够的：最后一个关键因素是教育和宣传，让公众了解这些原本看不见的项目。这个项目的理念很简单：如果这些数据池影响我们的生活，我们必须知道它们是什么以及它们做什么。该项目的技术重点包括干扰数据系统和合理测量结果。一些数据代理提供用户访问，允许对推断进行直接验证。该项目还包括创建“人物角色”。在数据池中留下痕迹的人工身份。如果数据代理购买该数据并对其进行操作，则会在数据源和数据使用者之间创建因果关系，从而允许在数据生态系统中对数据流进行归因。项目的其他部分包括直接从代理那里购买数据，评估这些代理可能带来的潜在损害，并故意播种多媒体内容，其中包括各种级别的可识别信息，以检测数据代理何时开始抓取这些多媒体源。

Our lives are surrounded by a constant web of data, picked up by a global network of unseen programs that gather, coalesce, combine, and merge every scrap of data they can acquire. These programs and companies operate out of public view, collecting and exchanging data for profit without clear public knowledge. This is a complex ecosystem, the original collectors of data are likely unaware of eventual uses, users of data may be unaware of the original source. This project seeks to illuminate this ecosystem through a series of experiments by attempting to measure and perturb unseen data pools by selectively adding or retrieving information. Additionally, this project focuses on creating traps and triggers, artificial data that future data providers might employ, enabling discovery of new collection and use of data. Finally, simply researching the phenomenon is insufficient: a final critical factor is education and outreach, empowering the public with an understanding of these otherwise unseen programs. The philosophy of this project is simple: If these data pools affect our lives, we must know what they are and what they do. The technical focus of this project involves perturbing the data systems and soundly measuring the results. Some data brokers provide user access, allowing the direct validation of inferences. The project also involves creating ?personas?, artificial identities designed to leave traces in data pools. If a data broker purchases and acts on this data, this creates a causal link between data source and data consumer, allowing attribution of data flows within the data ecosystem. Other portions of the project involve purchasing data directly from brokers, evaluating the potential damage that such brokers may entail, and deliberately seeding multimedia content which includes various levels of identifiable information to detect when data brokers begin scraping these multimedia sources.