Visible to the public TWC: TTP Option: Large: Collaborative: Towards a Science of Censorship ResistanceConflict Detection Enabled

Project Details

Lead PI

Performance Period

Sep 01, 2015 - Nov 30, 2016

Institution(s)

SUNY at Stony Brook

Award Number


Outcomes Report URL


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.