TWC: Small: Critter@home: Content-Rich Traffic Trace Repository from Real-Time, Anonymous, User Contributions

TWC：小型：Critter@home：来自实时、匿名、用户贡献的内容丰富的流量跟踪存储库

• 批准号: 1224035
• 负责人: Jelena Mirkovic
• 金额: $ 37.5万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1224035&HistoricalAwards=false
• 关键词: TWC; Small; Critter; home; Content

There are very few publicly available network traces that contain application-level data, because of the enormous privacy risk that sharing such data creates. Application-level data is rich with personal and private information, such as human names, social security numbers, etc. that criminals can monetize. Yet such data is necessary for realistic testing of research products, and for understanding trends in the domain of networking and network applications.This project develops a publicly accessible, diverse and fresh archive of content-rich network data, contributed by volunteer users, called Critter-at-home. Users join the Critter overlay whenever online, offering their data to interested researchers. Privacy of data contributors is protected by several means. First, contributors may opt to host their own data on their machines, thus retaining full control over it. Second, we process contributed data to modify all personal and private information (PPI) and we encrypt it. Third, no human apart from the contributor ever accesses the raw, PPI-sanitized, data. Instead, researchers query the data via our Critter-at-home framework, and they receive aggregate statistics (counts, distributions, etc.) of the traffic features they query for. Four, all contact with a contributor is at her discretion and is done through an anonymous network, where contributor identities are hidden.The archive this project creates will greatly advance security research by providing necessary data for its validation and for data mining. This archive will further be valuable to a broader networking e.g., for realistic traffic generation, as ground truth in traffic classification, and for many other purposes.

很少有包含应用程序级数据的公开可用网络跟踪，因为共享此类数据会产生巨大的隐私风险。应用程序级数据包含丰富的个人和私人信息，例如人的姓名、社会保险号等，犯罪分子可以利用这些信息获利。然而，这些数据对于研究产品的实际测试，以及理解网络和网络应用领域的趋势是必要的。该项目开发了一个可公开访问的、多样化的、内容丰富的网络数据的新鲜档案，由志愿者用户贡献，称为“居家动物”。用户可以随时在线加入Critter覆盖，将他们的数据提供给感兴趣的研究人员。数据提供者的隐私通过几种方式得到保护。首先，贡献者可以选择在自己的机器上托管自己的数据，从而保留对数据的完全控制。其次，我们处理贡献的数据来修改所有个人和私人信息（PPI），并对其进行加密。第三，除了贡献者之外，没有人访问过原始的、经过ppi处理的数据。相反，研究人员通过我们的critter -home框架查询数据，他们会收到他们查询的交通特征的汇总统计（计数，分布等）。第四，与投稿人的所有联系都由她自行决定，并通过匿名网络进行，投稿人的身份是隐藏的。这个项目创建的档案将通过为其验证和数据挖掘提供必要的数据，极大地推进安全性研究。该档案将进一步对更广泛的网络有价值，例如，用于现实的流量生成，作为流量分类中的地面真相，以及许多其他目的。