Botnet Detection Based on Network Behavior

Current techniques for detecting botnets examine traffic content for IRC commands, monitor DNS for strange usage, or set up honeynets to capture live bots. Our botnet detection approach is to examine flow characteristics such as bandwidth, packet timing, and burst duration for evidence of botnet command and control activity. We have constructed an architecture that first eliminates traffic that is unlikely to be a part of a botnet, classifies the remaining traffic into a group that is likely to be part of a botnet, then correlates the likely traffic to find common communications patterns that would suggest the activity of a botnet. Our results show that botnet evidence can be extracted from a traffic trace containing over 1.3 million flows.