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SDN-Assisted Network-Based Mitigation of Slow DDoS Attacks

  • Thomas Lukaseder
  • Lisa Maile
  • Benjamin Erb
  • Frank Kargl
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 255)

Abstract

Slow-running attacks against network applications are often not easy to detect, as the attackers behave according to the specification. The servers of many network applications are not prepared for such attacks, either due to missing countermeasures or because their default configurations ignores such attacks. The pressure to secure network services against such attacks is shifting more and more from the service operators to the network operators of the servers under attack. Recent technologies such as software-defined networking offer the flexibility and extensibility to analyze and influence network flows without the assistance of the target operator.

Based on our previous work on a network-based mitigation, we have extended a framework to detect and mitigate slow-running DDoS attacks within the network infrastructure, but without requiring access to servers under attack. We developed and evaluated several identification schemes to identify attackers in the network solely based on network traffic information. We showed that by measuring the packet rate and the uniformity of the packet distances, a reliable identificator can be built, given a training period of the deployment network.

Keywords

DDoS mitigation Slow-running DDoS attacks Slow HTTP Network-based mitigation Software-defined networking 

Notes

Acknowledgment

We like to thank the Student Union of Electrical Engineering (Fachbereichsvertretung Elektrotechnik) at Ulm University and Philipp Hinz in particular for providing the necessary data. This work was supported in the bwNET100G+ project by the Ministry of Science, Research and the Arts Baden-Württemberg (MWK). The authors alone are responsible for the content of this paper.

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018

Authors and Affiliations

  • Thomas Lukaseder
    • 1
  • Lisa Maile
    • 1
  • Benjamin Erb
    • 1
  • Frank Kargl
    • 1
  1. 1.Institute of Distributed SystemsUlm UniversityUlmGermany

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