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A Symptom based Taxonomy for Network Security

네트워크상에서의 징후를 기반으로 한 공격분류법

  • 김기윤 (성균관대학교 컴퓨터공학과) ;
  • 최형기 (성균관대학교 정보통신공학부 컴퓨터공학과) ;
  • 최동현 (성균관대학교 컴퓨터공학과) ;
  • 이병희 (성균관대학교 컴퓨터공학과) ;
  • 최윤성 (성균관대학교 컴퓨터공학과) ;
  • 방효찬 (ETRI 능동보안기술연구팀) ;
  • 나중찬 (ETRI 능동보안기술연구팀)
  • Published : 2006.08.01

Abstract

We present a symptom based taxonomy for network security. This taxonomy classifies attacks in the network using early symptoms of the attacks. Since we use the symptom it is relatively easy to access the information to classify the attack. Furthermore we are able to classify the unknown attack because the symptoms of unknown attacks are correlated with the one of known attacks. The taxonomy classifies the attack in two stages. In the first stage, the taxonomy identifies the attack in a single connection and then, combines the single connections into the aggregated connections to check if the attacks among single connections may create the distribute attack over the aggregated connections. Hence, it is possible to attain the high accuracy in identifying such complex attacks as DDoS, Worm and Bot We demonstrate the classification of the three major attacks in Internet using the proposed taxonomy.

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