| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | August 3, 2015 |
| Latest Amendment Date: | May 19, 2021 |
| Award Number: | 1518918 |
| Award Instrument: | Continuing Grant |
| Program Manager: |
Jeremy Epstein
CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | September 1, 2015 |
| End Date: | August 31, 2021 (Estimated) |
| Total Intended Award Amount: | $1,897,785.00 |
| Total Awarded Amount to Date: | $1,966,361.00 |
| Funds Obligated to Date: |
FY 2016 = $465,073.00 FY 2017 = $482,549.00 FY 2018 = $501,546.00 FY 2021 = $68,576.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
2150 SHATTUCK AVE BERKELEY CA US 94704-1345 (510)666-2900 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
CA US 94704-1159 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | Secure &Trustworthy Cyberspace |
| Primary Program Source: |
01001617DB NSF RESEARCH & RELATED ACTIVIT 01001718DB NSF RESEARCH & RELATED ACTIVIT 01001819DB NSF RESEARCH & RELATED ACTIVIT 01002122DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
The proliferation and increasing sophistication of censorship warrants continuing efforts to develop tools to evade it. Yet, designing effective mechanisms for censorship resistance ultimately depends on accurate models of the capabilities of censors, as well as how those capabilities will likely evolve. In contrast to more established disciplines within security, censorship resistance is relatively nascent, not yet having solid foundations for understanding censor capabilities or evaluating the effectiveness of evasion technologies. Consequently, the censorship resistance tools that researchers develop may ultimately fail to serve the needs of citizens who need them to communicate. Designers of these tools need a principled foundation for reasoning about design choices and tradeoffs.
To provide such a foundation, this project develops a science of censorship resistance: principled approaches to understanding the nature of censorship and the best ways to facilitate desired outcomes. The approach draws upon empirical studies of censorship as the foundation for models and abstractions to allow us to reason about the censorship-resistant technologies from first principles. The project aims to characterize and model censorship activities ranging from blocked search results to interference with international network traffic. The research develops theoretical models of censorship; reconciles these with large-scale empirical measurements; and uses these observations to design censorship-resistance tools to deploy in practice, as both components of Tor and standalone systems.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
This project aims to establish a scientific approach to understanding Internet censorship. Below is a short description of our notable achievements, for a complete list, visit Internet Freedom Science:
1. Developing and deploying technologies to evade censorship:
A highly valuable facet of our overall project is for us to have 'skin in the game" by developing circumvention technologies for real deployment. Doing so serves a vital role in closing the loop on our scientific methodologies, and enables us to observe empirically the full gamut of issues that come into play in the censor/evader arms race. To this end, we have further developed and operated the "meek" circumvention technique [1], which employs "domain fronting" to thwart blocking by censors, and now ships with the Tor Browser Bundle; and worked with an independent developer guiding the creation of "Snowflake", a mechanism by which users can contribute their browsers - even if operating behind NATs, as is very commonly the case - to serve as a massively diffuse collection of proxies to facilitate access to banned content [2].
2. Evaluating censorship circumvention technologies:
Effective evaluations of approaches to circumventing government Internet censorship require incorporating perspectives of how censors operate in practice. We conducted an extensive examination of real censors by surveying prior measurement studies and analyzing field reports and bug tickets from practitioners. We assessed both deployed circumvention approaches and research proposals to consider the criteria employed in their evaluations and compared these to the observed behaviors of real censors, identifying areas where evaluations could more faithfully and effectively incorporate the practices of modern censors [3].
3. Measuring censorship and internet blocking:
We seek to conduct ongoing, global measurements of reachability across the world to a wide range of Internet content [4-6]. Nominally such measurements would require vantage points spread across the entire Internet. We are developing three techniques: (1) based on IPID side channels ("Spooky Scan"); (2) one based on open DNS resolvers; (3) one based on cross-origin requests in HTTP (Encore). These mechanisms allow us to conduct third-party measurements: from our systems operating in the US, we can assess whether a remote country X blocks access to an arbitrary Internet resource Y, either by employing layer 3/4 blocking (measured by Spooky Scan) or by manipulating DNS responses.
We also measured the unintentional blocking of anti-censorship technologies, not by government censors, but by commercial entities. The second-class treatment of anonymous users ranges from outright rejection to limiting their access to a subset of the service's functionality or imposing hurdles such as CAPTCHA-solving. We conducted a study to methodically enumerate and characterize, in the context of Tor, the treatment of anonymous users as second-class Web citizens [6].
With many different kinds of internet blocking, web users do not receive clear messaging around who is doing the blocking, generating an ambiguity on the source of blocking. We develop a methodology to bring transparency around the source of blocking [8].
References:
1. David Fifield, Chang Lan, Rod Hynes, Percy Wegmann, and Vern Paxson. Blocking-resistant Communication through Domain Fronting Privacy Enhancing Technologies, 2015
2. https://snowflake.torproject.org/
3. Sok: Towards grounding censorship circumvention in empiricism. MC Tschantz, S Afroz, V Paxson. IEEE Symposium on Security and Privacy (SP), 2016
4. Paul Pearce, Roya Ensafi, Frank Li, Nick Feamster, and Vern Paxson
Augur: Internet-Wide Detection of Connectivity Disruptions. IEEE Symposium on Security and Privacy (SP), 2017
5. Paul Pearce, Roya Ensafi, Frank Li, Nick Feamster, and Vern Paxson. Toward Continual Measurement of Global Network-Level Censorship. IEEE Security & Privacy, 2018
6. Sheharbano Khattak, David Fifield, Sadia Afroz, Mobin Javed, Srikanth Sundaresan, Vern Paxson, Steven J. Murdoch, and Damon McCoy
Do You See What I See? Differential Treatment of Anonymous Users
Proceedings of the Network and Distributed System Security Symposium (NDSS), 2016
7. Meisam Navaki, Rajkumar Pandi, Michael Carl Tschantz, Jedidiah R. Crandall, King-wa Fu, Dahlia Qiu Shi, and Miao Sha. Assessing Post Deletion in Sina Weibo: Multi-modal Classification of Hot Topics. Second Workshop on NLP for Internet Freedom (NLP4IF), 2019
8. Asim Waheed (LUMS), Shoaib Asif Qazi (LUMS), Suleman Ahmad (UW Madison), Muhammad Abdullah (LUMS), Michael Tschantz (ICSI, Berkeley), Sadia Afroz (ICSI, Berkeley) and Mobin Javed (LUMS). Who is Blocking Me? Using Traceroutes to Locate and Attribute Blocking. Tech report, 2021.
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Last Modified: 03/04/2022
Modified by: Sadia Afroz
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