CAREER: Automatically Learning to Evade Internet Censorship

职业:自动学习逃避互联网审查

基本信息

  • 批准号:
    1943240
  • 负责人:
  • 金额:
    $ 49.96万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2020
  • 资助国家:
    美国
  • 起止时间:
    2020-10-01 至 2025-09-30
  • 项目状态:
    未结题

项目摘要

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.
互联网为开放的交流、外交和教育提供了前所未有的机遇。不幸的是,互联网的开放性受到了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者玩猫捉老鼠的游戏,开发新的计划来逃避审查者,而审查者又制定了越来越复杂的对策。长期以来,审查者在这场军备竞赛中一直有一个固有的优势:他们的系统细节通常不会公开,因此研究人员不得不经历手动、费力的步骤来衡量、创新、实施和测试新的规避技术。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,使快速发现逃避和理解民族国家审查的新方法自动化。该项目的最终目标是安全地得出规避/探测军备竞赛的合乎逻辑的结论--并为下一次军备竞赛做准备。该项目还包括一项教育计划,旨在通过探索扩大和扩大对本科生研究的参与,来应对计算机专业本科生入学人数的迅速增长。该项目提出了BreakerSpace,这是一个围绕本科团体研究项目设计的实验室,并将这些实验室整合到自动逃避审查的工作中。建议的研究遵循三个广泛的主题:(1)开发基于人工智能的新技术来自动逃避各种网络审查;(2)部署人工智能辅助审查逃避策略,并开发新的算法,通过协作的众包培训有效地扩大新策略的发现;(3)以前所未有的规模执行人工智能辅助的审查测量。拟议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者进行培训、评估、测量和部署,并向被审查的用户免费提供规避软件。如果成功,这个项目建立和部署的人工智能以及它所执行的衡量标准,将使人们能够更灵活地规避新形式的审查,并将更深入地了解审查机构是如何工作的、如何规避它们,以及它们如何随着时间的推移而更新。因此,这个项目有可能打破研究人员和审查制度几十年来一直从事的手动回避/检测循环,从而帮助世界各地的数百万用户实现信息的开放获取。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。

项目成果

期刊论文数量(13)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Detecting Network Interference Without Endpoint Participation
在没有端点参与的情况下检测网络干扰
Towards a Comprehensive Understanding of Russian Transit Censorship
全面了解俄罗斯的过境审查制度
Measuring and Evading Turkmenistan’s Internet Censorship: A Case Study in Large-Scale Measurements of a Low-Penetration Country
测量和规避土库曼斯坦的互联网审查:低渗透率国家大规模测量的案例研究
  • DOI:
    10.1145/3543507.3583189
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Nourin, Sadia;Tran, Van;Jiang, Xi;Bock, Kevin;Feamster, Nick;Hoang, Nguyen Phong;Levin, Dave
  • 通讯作者:
    Levin, Dave
A Global Measurement of Routing Loops on the Internet
  • DOI:
    10.1007/978-3-031-28486-1_16
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Abdulrahman Alaraj;Kevin Bock;Dave Levin;Eric Wustrow
  • 通讯作者:
    Abdulrahman Alaraj;Kevin Bock;Dave Levin;Eric Wustrow
Your Censor is My Censor: Weaponizing Censorship Infrastructure for Availability Attacks
  • DOI:
    10.1109/spw53761.2021.00059
  • 发表时间:
    2021-05
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Kevin Bock;Pranav Bharadwaj;Jasraj Singh;Dave Levin
  • 通讯作者:
    Kevin Bock;Pranav Bharadwaj;Jasraj Singh;Dave Levin
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David Levin其他文献

Analysis of Vitamin K1 in Soybean Seed: Assessing Levels in a Lineage Representing Over 35 Years of Breeding
大豆种子中维生素 K1 的分析:评估代表超过 35 年育种的谱系的水平
  • DOI:
    10.1007/s11746-016-2795-8
  • 发表时间:
    2016
  • 期刊:
  • 影响因子:
    0
  • 作者:
    M. M. Thompson;Ashley Niemuth;Jane Sabbatini;David Levin;Matthew L. Breeze;Xin Li;Tim Perez;M. Taylor;G. Harrigan
  • 通讯作者:
    G. Harrigan
Practical extrapolation methods: theory and applications
  • DOI:
  • 发表时间:
    2005
  • 期刊:
  • 影响因子:
    0
  • 作者:
    David Levin
  • 通讯作者:
    David Levin
Examining Food Store Scanner Data: A Comparison of the IRI InfoScan Data With Other Data Sets, 2008–2012
检查食品店扫描仪数据:IRI InfoScan 数据与其他数据集的比较,2008-2012 年
  • DOI:
  • 发表时间:
    2018
  • 期刊:
  • 影响因子:
    0
  • 作者:
    David Levin;Danton Noriega;C. Dicken;A. Okrent;M. Harding;Michael F. Lovenheim
  • 通讯作者:
    Michael F. Lovenheim
Training for the Future of Radiology: A Report of the 2005 Intersociety Conference
  • DOI:
    10.1016/j.jacr.2006.01.001
  • 发表时间:
    2006-05-01
  • 期刊:
  • 影响因子:
  • 作者:
    N. Reed Dunnick;Kimberly Applegate;Ronald Arenson;David Levin
  • 通讯作者:
    David Levin
A Microfluidic Platform for Evaluating Neutrophil Chemotaxis Induced by Sputum from COPD Patients
用于评估 COPD 患者痰液诱导的中性粒细胞趋化性的微流体平台
  • DOI:
  • 发表时间:
    2015
  • 期刊:
  • 影响因子:
    3.7
  • 作者:
    Jiandong Wu;Craig Hillier;P. Komenda;Ricardo Lobato de Faria;David Levin;Michael Ruogu Zhang;F. Lin
  • 通讯作者:
    F. Lin

David Levin的其他文献

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{{ truncateString('David Levin', 18)}}的其他基金

IMR: MT: A Tool for Passively Measuring Internet Censorship
IMR:MT:被动衡量互联网审查的工具
  • 批准号:
    2323193
  • 财政年份:
    2023
  • 资助金额:
    $ 49.96万
  • 项目类别:
    Standard Grant
CNS Core: Large: Collaborative Research: Towards an Evolvable Public Key Infrastructure
CNS 核心:大型:协作研究:迈向可进化的公钥基础设施
  • 批准号:
    1901325
  • 财政年份:
    2019
  • 资助金额:
    $ 49.96万
  • 项目类别:
    Continuing Grant
Tech+Research: Welcoming Women to Computing Research, Hackathon Style
技术研究:欢迎女性参与计算机研究,黑客马拉松风格
  • 批准号:
    1902304
  • 财政年份:
    2018
  • 资助金额:
    $ 49.96万
  • 项目类别:
    Standard Grant
SaTC: CORE: Small: Collaborative: Building Sophisticated Services with Programmable Anonymity Networks
SaTC:核心:小型:协作:使用可编程匿名网络构建复杂的服务
  • 批准号:
    1816802
  • 财政年份:
    2018
  • 资助金额:
    $ 49.96万
  • 项目类别:
    Standard Grant
TWC: Medium: Collaborative: Measuring and Improving the Management of Today's PKI
TWC:媒介:协作:衡量和改进当今 PKI 的管理
  • 批准号:
    1564143
  • 财政年份:
    2016
  • 资助金额:
    $ 49.96万
  • 项目类别:
    Continuing Grant
CSR: Medium: Collaborative Research: Towards Finer-grained Cloud Computing
CSR:媒介:协作研究:迈向更细粒度的云计算
  • 批准号:
    1409249
  • 财政年份:
    2014
  • 资助金额:
    $ 49.96万
  • 项目类别:
    Continuing Grant

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