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Detecting Abnormal Patterns of Network Traffic by Analyzing Linear Patterns and Intensity Features

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2012, 17(5), pp.21-28
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

Jang Seok-Woo 1 Gye-young Kim 2 Hyeon Suk Na ORD ID 2

1안양대학교
2숭실대학교

Accredited

ABSTRACT

Recently, the necessity for good techniques of detecting network traffic attack has increased. In this paper, we suggest a new method of detecting abnormal patterns of network traffic data by visualizing their IP and port information into two dimensional images. The proposed approach first generates four 2D images from IP data of transmitters and receivers, and makes one 2D image from port data. Analyzing those images, it then extracts their major features such as linear patterns or high intensity values, and determines if traffic data contain DDoS or DoS Attacks. To comparatively evaluate the performance of the proposed algorithm, we show that our abnormal pattern detection method outperforms the existing algorithm in terms of accuracy and speed.

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