Detecting Botnet Activities Based on Abnormal DNS traffic

نویسندگان

  • Ahmed M. Manasrah
  • Awsan Hasan
  • Omar Amer Abouabdalla
  • Sureswaran Ramadass
چکیده

The botnet is considered as a critical issue of the Internet due to its fast growing mechanism and affect. Recently, Botnets have utilized the DNS and query DNS server just like any legitimate hosts. In this case, it is difficult to distinguish between the legitimate DNS traffic and illegitimate DNS traffic. It is important to build a suitable solution for botnet detection in the DNS traffic and consequently protect the network from the malicious Botnets activities. In this paper, a simple mechanism is proposed to monitors the DNS traffic and detects the abnormal DNS traffic issued by the botnet based on the fact that botnets appear as a group of hosts periodically. The proposed mechanism is also able to classify the DNS traffic requested by group of hosts (group behavior) and single hosts (individual behavior), consequently detect the abnormal domain name issued by the malicious Botnets. Finally, the experimental results proved that the proposed mechanism is robust and able to classify DNS traffic, and efficiently detects the botnet activity with average detection rate of 89%. Keywords-Botnet detection, Network threat detection, Network worm detection.

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عنوان ژورنال:
  • CoRR

دوره abs/0911.0487  شماره 

صفحات  -

تاریخ انتشار 2009