Inference and analysis of formal models of botnet command and control protocols

We propose a novel approach to infer protocol state machines in the realistic high-latency network setting, and apply it to the analysis of botnet Command and Control (C &C) protocols. Our proposed techniques enable an order of magnitude reduction in the number of queries and time needed to learn a botnet C &C protocol compared to classic algorithms (from days to hours for inferring the MegaD C &C protocol). We also show that the computed protocol state machines enable formal analysis for botnet defense, including finding the weakest links in a protocol, uncovering protocol design flaws, inferring the existence of unobservable communication back-channels among botnet servers, and finding deviations of protocol implementations which can be used for fingerprinting. We validate our technique by inferring the protocol state-machine from Postfix's SMTP implementation and comparing the inferred state-machine to the SMTP standard. Further, our experimental results offer new insights into MegaD's C &C, showing our technique can be used as a powerful tool for defense against botnets.