The paper “Detecting Encrypted Botnet Traffic” was accepted by Global Internet 2013 in Turin, Italy (available at http://www.netsec.colostate.edu/~zhang/DetectingEncryptedBotnetTraffic.pdf)
From the abstract:
Bot detection methods that rely on deep packet in- spection (DPI) can be foiled by encryption. Encryption, however, increases entropy. This paper investigates whether adding high- entropy detectors to an existing bot detection tool that uses DPI can restore some of the bot visibility. We present two high-entropy classifiers, and use one of them to enhance BotHunter. Our results show that while BotHunter misses about 50% of the bots when they employ encryption, our high-entropy classifier restores most of its ability to detect bots, even when they use encryption.
This work is advised by Christos Papadopolous and Dan Massey at Colorado State University.