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Privacy-Preserving Anomaly Detection Across Multi-domain for Software Defined Networks

  • Huishan Bian
  • Liehuang Zhu
  • Meng Shen
  • Mingzhong Wang
  • Chang Xu
  • Qiongyu Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9565)

Abstract

Software Defined Network (SDN) separates control plane from data plane and provides programmability which adds rich function for anomaly detection. In this case, every organization can manage their own network and detect anomalous traffic data using SDN architecture. Moreover, detection of malicious traffic, such as DDoS attack, would be dealt with much higher accuracy if these organizations shared their data. Unfortunately, they are unwilling to do so due to privacy consideration. To address this contradiction, we propose an efficient and privacy-preserving collaborative anomaly detection scheme. We extend prior work on SDN-based anomaly detection method to guarantee accuracy and privacy at the same time. The implementation of our design on simulated data shows that it performs well for network-wide anomaly detection with little overhead.

Keywords

Privacy-preserving Multi-domain collaboration Anomaly detection Software defined network 

Notes

Acknowledgment

The research work reported in this paper is supported by National Science Foundation of China under Grant No. 61100172, 61272512, 61402037, Program for New Century Excellent Talents in University (NCET-12-0046), Beijing Natural Science Foundation No. 4132054, and Beijing Institute of Technology Research Fund Program for Young Scholars.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Huishan Bian
    • 1
  • Liehuang Zhu
    • 1
  • Meng Shen
    • 1
    • 2
  • Mingzhong Wang
    • 3
  • Chang Xu
    • 1
  • Qiongyu Zhang
    • 1
  1. 1.Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications, School of Computer ScienceBeijing Institute of TechnologyBeijingPeople’s Republic of China
  2. 2.Ministry of EducationKey Laboratory of Computer Network and Information Integration (Southeast University)NanjingPeople’s Republic of China
  3. 3.Faculty of Arts and BusinessUniversity of the Sunshine CoastQueenslandAustralia

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