Collaborative Behavior Visualization and Its Detection by Observing Darknet Traffic

  • Satoru Akimoto
  • Yoshiaki Hori
  • Kouichi Sakurai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7672)

Abstract

Recently, we have a problem about an attack generated by a botnet which consists of a group of compromised computers called bots. An attacker called botmaster controls it and a botnet invokes an attack such as scanning and DDoS attack. In this paper, we use the 3D-visualization to investigate the change of attack according to the darknet traffic. As a result, we discover the attack in which several source IP addresses transmit packets to a single destination within a short period of time. In addition, we find that the packet size and the destination port number are identical on its attack. Furthermore, we propose the method to detect this attack called behavior of collaborative attack. In our proposal, we focus on the number of source IP addresses which transmit packets to the single destination. We detected this packet and the rate of packet with the same packet size and destination port number occupied about 90% of the set unit of extracted packet.

Keywords

darknet collaborative behavior botnet 3D-visualization cybersecurity 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Satoru Akimoto
    • 1
    • 2
  • Yoshiaki Hori
    • 1
    • 2
  • Kouichi Sakurai
    • 1
    • 2
  1. 1.Graduate School of Information Science and Electrical EngineeringKyushu UniversityFukuokaJapan
  2. 2.Institute of Systems, Information Technologies and NanotechnologiesFukuokaJapan

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