AI기반 사이버 공격그룹 인프라 추적 시스템 개발
Development of AI-based Cyber Attack Group Infrastructure Tracking System (CGITS)
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초록
최근 국가 사이버 안보 환경의 급격한 변화에 따라, 대응 공백을 선제적으로조치하기 위해 적 사이버 공격그룹의 인프라, 공격 원점, 중계지, 공격 표면에서발생하는 통신 트래픽에 대한 정밀 분석이 요구된다. 이를 통해 활성화된공격자의 악성 행위와 사이버 공격자원을 빠르게 식별하고, 공격자원의 변화를추적 및 대응함으로써 작전적 시야를 확보하고 선제적인 전술적 작전 대응체계를구축할 수 있다. 본 논문에서는 사이버 공격 원점에서 목표지점의 공격 표면생성에 이르는 공격 인프라를 자동으로 탐지하고 식별하는 인공지능 기반 사이버공격그룹 인프라 추적 시스템(CGITS)을 제안한다. 개발 결과는 제안된 시스템이다양한 유형의 사이버 공격그룹을 식별하고, 추적하는 데 매우 효과적임을보여준다. 향후 CGITS의 설계 및 연구개발을 통해 시스템 개발이 완료될 경우, 민관군 영역에서 사이버 작전 간 적 사이버 공격자원을 빠르게 식별 및인식하고, 자원의 변화를 추적 및 대응함으로써 작전적 시야를 확보하고선제적인 전술적 사이버 작전 대응이 가능할 것으로 기대된다.
Abstract
In response to the rapid changes in the national cybersecurity environment and to proactively address potential response gaps, it is imperative to conduct a precise analysis of communication traffic originating from adversary cyber attack groups' infrastructure, attack origins, relay points, and attack surfaces. Such analysis enables the rapid identification of activated malicious activities and cyber attack resources, as well as tracking and responding to changes in these resources. This facilitates operational situational awareness and the establishment of proactive tactical operational response systems. This paper proposes an AI-based Cyber Attack Group Infrastructure Tracking System (CGITS) that automatically detects and identifies attack infrastructures from the attack origin to the generation of attack surfaces at target points. The successful design and development of CGITS is expected to enable rapid identification and recognition of adversary cyber attack resources in civilian, governmental, and military domains. Additionally, it will allow for tracking and responding to changes in these resources, thereby securing operational situational awareness and enabling proactive tactical cyber operation responses.
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