Abstract

A Redirection Botnet (RBnet) is a vast collection of compromised computers (called bots) used as a redirection/proxy infrastructure and under the control of a botmaster. We present the design, implementation and evaluation of a system called Redirection Botnet Seeker (RB-Seeker) for automatic detection of RBnets by utilizing three cooperating subsystems. Two of the subsystems are used to generate a database of domains participating in redirection: one detects redirection bots by following links embedded in spam emails, and the other detects redirection behavior based on network traces at a large university edge router using sequential hypothesis testing. The database of redirection domains generated by these two subsystems is fed into the final subsystem, which then performs DNS query probing on the domains over time. Based on certain behavioral attributes extracted from the DNS queries, the final subsystem makes use of a 2-tier detection strategy utilizing hyperplane decision functions. This allows it to quickly identify aggressive RBnets with a low false-positive rate (< 0.008%), while also accurately detecting stealthy RBnets (i.e., those mimicking valid DNS behavior, such as CDNs) by monitoring their behavior over time. Using DNS behavior as a means of detecting RBnets, RB-Seeker is impervious to the botmaster’s choice of Command-and-Control (C&C) channel (i.e., how the botmaster communicates and controls the bots) or use of encryption. 1

Citations