Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Modelling of Artificial Immune System for Development of Computer Immune system and Self Recognition Algorithm

컴퓨터 면역시스템 개발을 위한 인공면역계의 모델링과 자기인식 알고리즘

  • 심귀보 (중앙대학교 전자전기공학부) ;
  • 서동일 (한국전자통신연구원 정보보호기술 연구본부) ;
  • 김대수 (한신대학교 컴퓨터학과) ;
  • 임기욱 (선문대학교 산업공학과)
  • Published : 2002.02.01
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Abstract

According as many people use a computer newly, damage of computer virus and hacking is rapidly increasing by the crucial users. A computer virus is one of program in computer and has abilities of self reproduction and destruction like a virus of biology. And hacking is to rob a person's data in a intruded computer and to delete data in a Person s computer from the outside. To block hacking that is intrusion of a person's computer and the computer virus that destroys data, a study for intrusion detection of system and virus detection using a biological immune system is in progress. In this paper, we make a model of positive and negative selection for self recognition which have a similar function like T-cytotoxic cell that plays an important role in biological immune system. We embody a self-nonself distinction algorithm in computer, which is an important part when we detect an infected data by computer virus and a modified data by intrusion from the outside. And we showed the validity and effectiveness of the proposed self recognition algorithm by computer simulation about various infected data obtained from the cell change and string change in the self file.

최근 컴퓨터의 사용이 보편화되면서 악의적 사용자에 의해 발생하는 컴퓨터 바이러스와 해킹에 의한 피해가 급속히 증가하고 있다. 남의 컴퓨터에 침입하는 해킹이나 데이터를 파괴하는 컴퓨터 바이러스에 의한 피해를 막기 위해 최근에 생명체의 면역시스템의 특징을 이용해 인공면역계를 구성해 시스템 침입탐지와 바이러스 탐지 및 치료에 대한 연구가 활발히 진행 중에 있다. 생체 면역계는 외부에서 침입해 세포나 장기에 피해를 주는 물질인 항원을 스스로 자기세포와 구분해 인식.제거하는 기능이 있다. 이러한 면역계의 특징인 항원을 인식하는 기능은 자기세포의 확실한 인식을 가지고 있는 상태에서 다른 물질을 구분하는 자기.비자기 인식방법으로 똘 수 있다. 본 논문에서는 생체 면역계에서 세포독성 T세포의 생성과정의 하나인 Negative 및 Positive Selection을 모델링하여 침입에 의한 데이터 변경과 바이러스에 의한 데이터 감염 등을 탐지할 때 가장 중요한 요소인 자기 인식 알고리즘을 구현한다. 제안한 알고리즘은 큰 파일에서의 Detection을 구성하기 용이한 점을 가지며 국소(cell)변경과 블록(string)변경에 대한 자기인식률을 통해 알고리즘의 유효성을 검증한다.

Keywords

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