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Distributed denial of service attack defence simulation based on honeynet technology

  • Xiaoying Wang
  • Na Guo
  • Fangping GaoEmail author
  • Jilin Feng
Original Research

Abstract

Distributed denial of service (DDoS) is one of the main threats of Internet security, and the detection and prevention of DDoS has always been a hot issue in network security research. DDoS detection and defence systems have many shortcomings such as high false positive rate, low execution efficiency, and lack of linkage between detection and defence. Therefore, eliminating false positives, improving execution efficiency, and enhancing the linkage between detection and defence processes have always been the focuses of research. A preventive defence mechanism based on honeynet technology in the paper is presented without more additional equipment which does not rely on resource advantages, and is equally effective with less effort. Firstly, the in-depth analysis and discussion of detection and defence problems are illustrated by combining with the principle and characteristics of the attack, and systematically analyzing and classifing the detection and defence problems. Next, a distributed denial of service attack defence based on honeynet technology is proposed. Finally, algorithm and the effectiveness of the method are proved by simulation experiments.

Keywords

Distributed denial of service Attack defence simulation Honeynet technology 

Notes

Acknowledgements

The work is partially supported by (1) Langfang Science and Technology Research Self-financing Project, Research on Network Abnormal Behavior Analysis Technology Based on Traffic Precursor Observation System Flow Detection (Grant no. 2015013011), (2) Hebei Science and Technology Plan Project, Research on APT Attack Detection Algorithm Based on Big Data Analysis (Grant no. 16210705), (3) Shanghai Key Laboratory of Integrated Administration Technologies for Information Security, Research on Path Marking Method of Malicious Code Attack Based on CampusNetwork (Grant no. AGK201704), (4) Research on the basic research business expenses of the central colleges and universities, based on the full-campus network DNS, the key technology of malicious domain name automatic detection (Grant no. ZY20180123).

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Xiaoying Wang
    • 1
  • Na Guo
    • 1
  • Fangping Gao
    • 1
    Email author
  • Jilin Feng
    • 1
  1. 1.School of Information EngineeringInstitute of Disaster PreventionSanheChina

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