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Marionette: A Programmable Network Traffic Obfuscation System
Kevin P. Dyer, Portland State University; Scott E. Coull, RedJack LLC.; Thomas Shrimpton, Portland State University
Recently, a number of obfuscation systems have been developed to aid in censorship circumvention scenarios where encrypted network traffic is filtered. In this paper, we present Marionette, the first programmable network traffic obfuscation system capable of simultaneously controlling encrypted traffic features at a variety of levels, including ciphertext formats, stateful protocol semantics, and statistical properties. The behavior of the system is directed by a powerful type of probabilistic automata and specified in a user-friendly domain-specific language, which allows the user to easily adjust their obfuscation strategy to meet the unique needs of their network environment. In fact, the Marionette system is capable of emulating many existing obfuscation systems, and enables developers to explore a breadth of protocols and depth of traffic features that have, so far, been unattainable. We evaluate Marionette through a series of case studies inspired by censor capabilities demonstrated in the real-world and research literature, including passive network monitors, stateful proxies, and active probing. The results of our experiments not only show that Marionette provides outstanding flexibility and control over traffic features, but it is also capable of achieving throughput of up to 6:7Mbps when generating RFCcompliant cover traffic.
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