Award Abstract # 1518845
TWC: TTP Option: Large: Collaborative: Towards a Science of Censorship Resistance

NSF Org: CNS
Division Of Computer and Network Systems
Recipient: THE RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK
Initial Amendment Date: August 3, 2015
Latest Amendment Date: July 11, 2016
Award Number: 1518845
Award Instrument: Continuing Grant
Program Manager: Nina Amla
namla@nsf.gov
 (703)292-7991
CNS
 Division Of Computer and Network Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: September 1, 2015
End Date: November 30, 2016 (Estimated)
Total Intended Award Amount: $324,029.00
Total Awarded Amount to Date: $156,550.00
Funds Obligated to Date: FY 2015 = $76,778.00
FY 2016 = $2,764.00
History of Investigator:
  • Phillipa Gill (Principal Investigator)
    phillipa@cs.umass.edu
Recipient Sponsored Research Office: SUNY at Stony Brook
W5510 FRANKS MELVILLE MEMORIAL LIBRARY
STONY BROOK
NY  US  11794-0001
(631)632-9949
Sponsor Congressional District: 01
Primary Place of Performance: SUNY at Stony Brook
Department of Computer Science
Stony Brook
NY  US  11794-4400
Primary Place of Performance
Congressional District:
01
Unique Entity Identifier (UEI): M746VC6XMNH9
Parent UEI: M746VC6XMNH9
NSF Program(s): Secure &Trustworthy Cyberspace
Primary Program Source: 01001516DB NSF RESEARCH & RELATED ACTIVIT
01001617DB NSF RESEARCH & RELATED ACTIVIT

01001718DB NSF RESEARCH & RELATED ACTIVIT

01001819DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7434, 7925, 9102
Program Element Code(s): 806000
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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Bridger Hahn, Rishab Nithyanand, Phillipa Gill, and Rob Johnson "Castle: A Video Game-based Covert Channel" In IEEE European Symposium on Security and Privacy (Euro S&P) , 2016 http://www3.cs.stonybrook.edu/~phillipa/papers/castle.pdf
Rishab Nithyanand, Oleksii Starov, Adva Zair, Phillipa Gill, and Michael Schapira "Astoria: AS-aware relay selection for Tor" NDSS Symposium , 2016 http://www3.cs.stonybrook.edu/~phillipa/papers/astoria.pdf

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