Detecting Infected Botnet Machines by Using the Traffic Behavior Analysis

Fahimeh Hasani, Ebrahim Mahdipour


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.


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

Full Text:


Lululemon Black Friday cheap nfl jerseys Lululemon factory Outlet ny Black Friday discount tiffany outlet wholesale soccer jerseys online oakley black friday cheap nhl jerseys china cheap nfl jerseys north face black friday sale cheap nfl jerseys online Jordans Black Friday Sale 2015 Cheap Moncler Cyber Monday moncler outlet cheap soccer jerseys moncler outlet black friday cheap authentic nfl jerseys north face cyber monday Louboutin Black Friday canada wholesale cheap nfl jerseys lululemon cyber monday 2015 cheap nfl jerseys from china 2015 Cheap Moncler Black Friday Sale Moncler Cyber Monday 2015 cheap jerseys Lululemon Cyber Monday Sale jordans cyber monday deals 2015 cheap nike nfl jerseys Black Friday deals Lululemon 2015 jordan black friday 2015 Moncler Jackets Black Friday Sale 2015 Louboutin Pas Cher Black Friday 2015 Canada Lululemon north face black friday cheap wholesale soccer jerseys