Detecting DDoS attacks using conditional entropy

@article{Liu2010DetectingDA,
  title={Detecting DDoS attacks using conditional entropy},
  author={Yun Liu and Jieren Cheng and Jianping Yin and Boyun Zhang},
  journal={2010 International Conference on Computer Application and System Modeling (ICCASM 2010)},
  year={2010},
  volume={13},
  pages={V13-278-V13-282}
}
Distributed denial of service (DDoS) attacks is one of the major threats to the current Internet. After analyzing the characteristics of DDoS attacks and the existing approaches to detect DDoS attacks, a novel detection method based on conditional entropy is proposed in this paper. First, a group of statistical features based on conditional entropy is defined, which is named Traffic Feature Conditional Entropy (TFCE), to depict the basic characteristics of DDoS attacks, such as high traffic… CONTINUE READING

From This Paper

Figures, tables, and topics from this paper.
3 Citations
10 References
Similar Papers

References

Publications referenced by this paper.
Showing 1-10 of 10 references

A tutorial on support vector machines for pattern recognition [J

  • C. Burger
  • Data Mining and Knowledge Discovery. vol. 2(2…
  • 1998
Highly Influential
9 Excerpts

Detecting Distributed Denial of Service Attacks Based on Time Series Analysis

  • Q. D. Sun, D. Y. Zhang, P. Gao
  • Chinese Journal of Computers, vol.28(5), pp.767…
  • 2005
2 Excerpts

Similar Papers

Loading similar papers…