Detecting Infected Botnet Machines by Using the Traffic Behavior Analysis

Fahimeh Hasani, Ebrahim Mahdipour

Abstract


Despite the increase in attacks and other security challenges in cyberspace, we require new methods of detection and to develop new techniques for the new generations of attacks. One of these new threats are botnets. This article presents the means for identifying infected machines with botnets by using a behavioral analysis method. Work with botnets as a tool intended to carry out criminal activities has increased with large area in computer networks against large targets. The pattern of behavior By frequent studying on the nods and the visualization of traffic with FroceAtlas2 and Page Rank algorithms have been presented by analyzing the data traffic, as a result, the nodes that have the most interaction structure on bot in the network, have been identified as the machines infected with botnets.

Keywords


Botnets; traffic analysis; network traffic visualization; infected machines; data visualization

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