Defending DDoS Attacks Using Hidden Markov Models and Cooperative Reinforcement Learning

@inproceedings{Xu2007DefendingDA,
  title={Defending DDoS Attacks Using Hidden Markov Models and Cooperative Reinforcement Learning},
  author={Xin Xu and Yongqiang Sun and Zunguo Huang},
  booktitle={PAISI},
  year={2007}
}
In recent years, distributed denial of service (DDoS) attacks have brought increasing threats to the Internet since attack traffic caused by DDoS attacks can consume lots of bandwidth or computing resources on the Internet and the availability of DDoS attack tools has become more and more easy. However, due to the similarity between DDoS attack traffic and transient bursts of normal traffic, it is very difficult to detect DDoS attacks accurately and quickly. In this paper, a novel DDoS… CONTINUE READING

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Lifting the Smokescreen: Detecting Underlying Anomalies During a DDoS Attack

  • 2018 IEEE International Conference on Intelligence and Security Informatics (ISI)
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DeepDefense: Identifying DDoS Attack via Deep Learning

  • 2017 IEEE International Conference on Smart Computing (SMARTCOMP)
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