Automatically Learning How to Evade Censorship

Automatically Learning How to Evade Censorship

Abstract: Evading network censorship by nation-states has long been a slow, laborious process.  It takes researchers and activists much longer to understand how censors work and develop evasion strategies for them than it takes the censors to update their systems.  In this talk, I will present a genetic algorithm that automatically discovers how to evade censors.  Our tool, Geneva (Gen-etic Eva-sion) has to date discovered dozens of new ways to evade censors in China, India, Iran, and Kazakhstan.  Critically, it does so quickly, without typical human bias, and for a wide range of protocols and deployments.  Geneva has also discovered the first purely "server-side" evasion strategies, allowing clients to evade censorship without having to install any extra software whatsoever.

Project website: https://censorship.ai

Bio: Dave Levin is an assistant professor of Computer Science at the University of Maryland, where he also earned his PhD. He received an NSF CAREER award, multiple best-paper awards, and was recently recognized by the National Center for Women & Information Technology with an Undergraduate Research Mentoring award.  Dave started the Breakerspace lab at UMD, in which he advises dozens of undergraduate research groups in various projects in network and systems security.  https://www.cs.umd.edu/~dml