Network Traffic Anomaly Detection Based on N-ARMA Model

نویسندگان

  • Pingping Gu
  • Shijing Zhang
  • Zhimin Huang
  • Qingfeng Wu
چکیده

With the rapid development of the Internet and the continuous expanding of the data network, little potential anomaly can seriously affect the normal operation of the network, and even lead to huge economic losses. In order to be more accurate and efficient in the traffic detection, in this paper, we propose an N-ARMA based traffic anomaly detection model. We also conduct extensive experiments to verify the higher accurate ratio and recall ratio of our model by comparing with other traffic anomaly detection methods.

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تاریخ انتشار 2016