한국컴퓨터정보학회논문지 (Journal of the Korea Society of Computer and Information)

  • 제19권4호
  • /
  • Pages.81-90
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  • 2014
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  • 1598-849X(pISSN)
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  • 2383-9945(eISSN)
한국컴퓨터정보학회 (Korean Society of Computer Information)
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모바일 봇넷 탐지를 위한 HMM과 SVM 기법의 비교

Comparison of HMM and SVM schemes in detecting mobile Botnet

  • 최병하 (단국대학교 정보통신융합기술연구원) ;
  • 조경산 (단국대학교 소프트웨어학과)
  • Choi, Byungha (Research Institute of Information and Communication Convergence Technology) ;
  • Cho, Kyungsan (Dept. of Software Science, Dankook University)
  • 투고 : 2013.12.05
  • 심사 : 2014.03.02
  • 발행 : 2014.04.30
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초록

스마트폰 같은 모바일 장치의 대중적 보급과 발전으로 인해 PC 기반의 악성코드가 모바일 기반으로 빠르게 이동하고 있다. 특히 봇넷은 PC에서의 강력한 악성행위와 피해를 모바일 장치에서 재생산하며 새로운 기법을 추가하고 있다. 기존 PC 기반의 봇넷과 달리 모바일 봇넷은 동시에 다양한 공격 경로의 탐지가 어려워 네트워크 기반보다는 호스트 기반의 탐지 기법이 주를 이루고 있다. 본 논문에서는 호스트 기반 기법의 한계를 극복하기 위하여 네트워크 기반으로 모바일 봇넷을 탐지하는 HMM과 SVM을 적용한 2 가지 기법을 비교한다. 기계학습에 많이 사용되는 시계열 데이터와 단위시간 데이터를 추출하여 두 기법에 적용하여, 실제 봇넷이 설치된 환경의 트래픽 검증 분석을 통해 이들 데이터에 따른 두 기법의 탐지율과 탐지 특성을 제시한다.

As mobile devices have become widely used and developed, PC based malwares can be moving towards mobile-based units. In particular, mobile Botnet reuses powerful malicious behavior of PC-based Botnet or add new malicious techniques. Different from existing PC-based Botnet detection schemes, mobile Botnet detection schemes are generally host-based. It is because mobile Botnet has various attack vectors and it is difficult to inspect all the attack vector at the same time. In this paper, to overcome limitations of host-based scheme, we compare two network-based schemes which detect mobile Botnet by applying HMM and SVM techniques. Through the verification analysis under real Botnet attacks, we present detection rates and detection properties of two schemes.

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참고문헌

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피인용 문헌

  1. 준지도 지지 벡터 회귀 모델을 이용한 반응 모델링 vol.19, pp.9, 2014, https://doi.org/10.9708/jksci.2014.19.9.125