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A Robust and Efficient Detection Model of DDoS Attack for Cloud Services

  • Jian Zhang
  • Ya-Wei Zhang
  • Jian-Biao HeEmail author
  • Ou Jin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9530)

Abstract

Recently, DDoS attacks have become a major security threat to cloud services. How to detect and defend against DDoS attacks is currently a hot topic in both industry and academia. In this paper, we propose a novel model to detect DDoS attacks and identify attack packets for abnormal traffic filtering. The novelties of the model are that: (1) combined with the characteristics of three types of IP spoofing-based attacks and temporal correlation of transport layer connection state, a set of accurate check rules for abnormal packets are designed; (2) by improving the Bloom Filter algorithm, the efficient mapping mechanism of TCP2HC/UDP2HC and the reliable two-way checking mechanism of abnormal data packet are implemented; (3) DDoS attacks detection and filtering are realized by using non-parameter CUSUM algorithm to model the growth scale of abnormal packets. Experiments show that no matter what type of IP spoofing technology and the attack traffic scale, detection model can accurately detect the DDoS attacks as early as possible.

Keywords

DDoS IP spoofing HOP COUNT Check CUSUM 

Notes

Acknowledgment

This work is partially supported by the Planned Science and Technology Project of Hunan Province, China (NO.2015JC3044), and the National Natural Science Foundation of China (NO.61272147).

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Jian Zhang
    • 1
  • Ya-Wei Zhang
    • 1
  • Jian-Biao He
    • 1
    Email author
  • Ou Jin
    • 1
  1. 1.School of Information Science and EngineeringCentral South UniversityChangshaChina

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