NeTS: Large: Measuring and Modeling Internet Choke Points as Threats to Online Freedom

关于互联网瓶颈的紧迫政策问题，例如关于互联网巴尔干化或特定政策可能产生的影响的问题，很难回答，原因有二。 首先，现有数据通常仅限于一个国家或互联网的一小部分，时间很短。 第二，这些数据不适合简单的分析，如平均值或直接比较。 需要进行研究，弥合收集长期、大规模数据与回答决策者不断发展的高层次问题之间的差距。 该项目开发了先进的能力，用于测量互联网瓶颈，并以告知真实的政策问题的方式分析和建模数据。 该项目在网络堆栈的多个层（包括TCP/IP层过滤和社交媒体过滤）中纵向和全球范围内进行互联网阻塞点测量。 该项目还研究了隧道和网络虚拟化在不同国家和组织如何实施阻塞点方面的作用，以便有实施政策的中心位置。 为了实现这些目标，该项目正在开发先进的TCP/IP侧通道技术，用于测量TCP/IP层过滤和理解网络拓扑，新颖的推理算法和自然语言处理技术，以识别社交媒体的微妙操纵，以及基于Agent的建模的强大建模技术，以有意义的方式分析数据。 就更广泛的影响而言，该项目将提供新的能力：（a）向政策制定者通报数字言论自由受到侵犯或威胁的情况，（B）就如何绕过阻塞点和限制对世界各地公民的报复，向民主和反阻塞点工作提供建议。 作为该项目一部分开发的所有源代码将在GNU公共许可证（GPL）许可下发布，数据集将公开提供。 拟议项目的一个关键部分是指导研究生和本科生研究人员在研究的各个方面，并招聘和推广到新墨西哥州的初中和高中学生。 新墨西哥州的大学是卡内基RU/VH非常高的研究活动大学和一个HACU西班牙裔服务机构以及EPSCoR状态。 这使得UNM处于一个独特的位置，涉及在计算机科学中代表性不足的群体，真正处于经济劣势，在世界级的互联网测量研究。

Pressing policy questions with respect to Internet chokepoint, such as questions about Internet balkanization or the effects that a specific policy might have, are difficult to answer for two reasons. First, the data available are typically limited to a single country or small cross-section of the Internet for a short period of time. Second, the data do not lend themselves well to simple analysis such as averages or direct comparisons. Research is needed that bridges the gap between collecting long-term, wide-scale data and answering the ever-evolving high level questions that policy makers have. This project develops advanced capabilities for measuring Internet chokepoints and analyzing and modeling the data in a way that informs real policy questions. This project is carrying out Internet chokepoint measurements longitudinally and on a global scale, in multiple layers of the network stack including both TCP/IP layer filtering and filtering in social media. The project also studies the role of tunnels and network virtualization in how different countries and organizations implement chokepoints in order to have central locations for implementing policy. In order to accomplish these goals, the project is developing advanced TCP/IP side channel techniques for measuring TCP/IP layer filtering and understanding network topology, novel inference algorithms and natural language processing techniques to discern subtle manipulations of social media, and robust modeling techniques based on Agent Based modeling to analyze the data in a meaningful way. In terms of broader impacts, the project will provide new capabilities: (a) to inform policy makers about violations or threats to digital speech freedom, and (b) to advise democratic and anti-chokepoint efforts on how to circumvent chokepoints and limit retributions to citizens around the world. All source code developed as part of this project will be released under a GNU Public License (GPL) license, and the datasets will be made publicly available. A key part of the proposed project is mentorship of graduate and undergraduate researchers in all aspects of research, and recruitment and outreach to middle- and high-school students in New Mexico. The University of New Mexico is both a Carnegie RU/VH Very High Research Activity University and a HACU Hispanic Serving Institution as well as an EPSCoR state. This puts UNM in a unique position to involve groups that are underrepresented in computer science, and truly disadvantaged economically, in world-class Internet measurement research.