Earticle

초록

영어

Anomaly traffic detecting using Netflow data is one of important problems in the field of network security. In this paper, we proposed an approach using MapReduce model, which was realized by means of the entropy observation and DFN (Distinct feature number) distribution deviations of traffic features under anomalies at small time scales. The MapReduce was used to deal with huge amounts of data with the aid of computer cluster processing. Experimental results show the effectiveness of the proposed approach.

목차

Abstract
 1. Introduction
 2. Formatting your Paper
 3. Implementation of the Anomaly Traffic Detecting Method
  3.1. The Network Traffic Features in Anomaly Traffic Detection
  3.2. Implementation using MapReduce
 4. Simulation
 5. Conclusion
 Acknowledgement
 References

키워드

저자

• Wang Jin-Song [ School of Computer and Communication Engineering, Tianjin University of Technology, Tianjin 300384 ]
• Zhang Long [ School of Computer and Communication Engineering, Tianjin University of Technology, Tianjin 300384 ]
• Shi Kai [ School of Computer and Communication Engineering, Tianjin University of Technology, Tianjin 300384 ]
• Zhang Hong-hao [ School of Computer and Communication Engineering, Tianjin University of Technology, Tianjin 300384 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Security and Its Applications

• 간기

  격월간

• pISSN

  1738-9976

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605