CAREER: Automatically Learning to Evade Internet Censorship

互联网为开放的沟通、外交和教育提供了前所未有的机会。不幸的是，互联网的开放性受到世界各地强国的挑战，这些国家今天在全国范围内对互联网流量进行审查。 几十年来，安全研究人员一直在与审查机构玩猫捉老鼠的游戏，开发新的计划来逃避审查机构，而审查机构反过来又开发出越来越复杂的对策。 在这场军备竞赛中，审查机构长期以来一直具有固有的优势：他们的系统的细节通常不会公开，因此研究人员不得不经历手动的、艰苦的测量、创新、实施和测试新的规避技术的步骤。 该项目提出了一个雄心勃勃的研究议程，旨在开发人工智能，以自动快速发现逃避和理解民族国家审查的新方法。 该项目的最终目标是安全地达到规避/探测军备竞赛的逻辑结论，并为下一次军备竞赛做好准备。 该项目还包括一项教育计划，旨在通过探索扩大和扩大本科研究参与的方法，解决本科计算机科学课程入学人数迅速上升的问题。 该项目提出了Breakerspace，一个围绕本科生群体研究项目设计的实验室，并将这些项目整合到自动化审查规避的工作中。拟议的研究遵循三个主要目标：（1）开发基于人工智能的新技术，以自动规避各种网络审查，（2）部署人工智能辅助的审查规避策略，并开发新算法，通过协作，众包培训，以及（3）以前所未有的规模进行人工智能辅助的审查测量。 拟议中的研究计划采取了一种实用的方法--针对真实的民族国家审查员进行培训、评估、测量和部署，并为受审查的用户免费提供规避软件。 如果成功，该项目构建和部署的人工智能及其执行的测量将能够更灵活地规避新形式的审查，并将更深入地了解审查员如何（失败）工作，如何绕过它们，以及它们如何随着时间的推移而更新。 因此，该项目有可能打破研究人员和审查制度数十年来一直从事的手动规避/检测循环，从而帮助世界各地数百万用户实现信息的开放访问。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The Internet provides unprecedented opportunities for open communication, diplomacy, and education. Unfortunately, the openness of the Internet is challenged by powerful countries around the world who today engage in nationwide censorship of Internet traffic. For decades, security researchers have engaged in a cat-and-mouse game with censors, developing new schemes to evade censors, who in turn have developed increasingly sophisticated countermeasures. Censors have long had an inherent advantage in this arms race: details of their systems are typically not made publicly known, and thus researchers have had to undergo manual, laborious steps of measuring, innovating, implementing, and testing for new evasion techniques. This project proposes an ambitious research agenda towards developing artificial intelligence to automate the rapid discovery of new methods for evading and understanding nation-state censors. The ultimate goal of the project is to safely reach the logical conclusion of the evade/detect arms race--and to prepare for the next one. This project also includes an education plan that seeks to address the meteoric rise of enrollment in undergraduate computer science programs, by exploring ways to scale-up and broaden participation in undergraduate research. The project proposes Breakerspace, a lab designed around group undergraduate research projects, and integrates these into the work on automating censorship evasion.The proposed research follows three broad thrusts: (1) Developing new AI-based techniques for automatically evading in-network censors of various kinds, (2) Deploying AI-assisted censorship evasion strategies and developing new algorithms to efficiently scale-up discovery of new strategies via collaborative, crowd-sourced training, and (3) Performing AI-assisted measurement of censorship at unprecedented scale. The proposed research plan takes a practical approach--training, evaluating, measuring, and deploying against real nation-state censors, and making evasion software freely available for censored users. If successful, the AI this project builds and deploys, and the measurements it performs, will enable more agile evasion of new forms of censorship, and will lend deeper insight into how censors (fail to) work, how to circumvent them, and how they update over time. As a result, this project has the potential to break the manual evade/detect cycle that researchers and censoring regimes have engaged in for decades, thereby assisting millions of users around the world in achieving open access to information.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.