DOI QR코드

DOI QR Code

사물인터넷 환경에서의 VPN-Filter malware 기술과 대응방법

VPN-Filter Malware Techniques and Countermeasures in IoT Environment

  • 김승호 (백석대학교 정보통신학부) ;
  • 이근호 (백석대학교 정보통신학부)
  • Kim, Seung-Ho (Division of Information Communication, Baek-seok University) ;
  • Lee, Keun-Ho (Division of Information Communication, Baek-seok University)
  • 투고 : 2018.10.22
  • 심사 : 2018.12.20
  • 발행 : 2018.12.31

초록

최근 정보통신기술의 빠른 발전에 따라 새로운 유형의 취약점 및 공격 기법들이 수없이 생겨나고 사회적인 물의를 일으키고 있다. 본 논문에서는 2018년 5월경 Cisco 위협 정보팀인 Talos Intelligence가 새롭게 발견한 대규모 사물인터넷 기반 botnet을 구성하는 'VPN-Filter'의 공개된 표본을 분석하여, 현시대의 사물인터넷 기반 botnet의 구성 방식과 공격방식에 대하여 살펴보고 해당 자료를 바탕으로 VPN-Filter와 접목해 VPN-Filter의 공격 시나리오와 공격 취약점의 특징에 대해 이해하고 VPN-Filter 악성코드를 이용한 Botnet 구성의 핵심이 되는 C&C Server 연결방식의 원인을 제거하기 위해 EXIF 메타데이터 제거 방식을 통한 해결방안을 제안하여 미래에 다가올 4차 산업혁명 시대의 사이버 보안에 기여하길 기대한다.

Recently, a wide variety of IoT environment is being created due to the rapid development of information and communication technology. And accordingly in a variety of network structures, a countless number of attack techniques and new types of vulnerabilities are producing a social disturbance. In May of 2018, Talos Intelligence, the Cisco threat intelligence team has newly discovered 'VPN-Filter', which constitutes a large-scale IoT-based botnet, is infecting consumer routers in over 54 countries around the world. In this paper, types of IoT-based botnets and the attack techniques utilizing botnet will be examined and the countermeasure technique through EXIF metadata removal method which is the cause of connection method of C & C Server will be proposed by examining the characteristics of attack vulnerabilities and attack scenarios of VPN-Filter.

키워드

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Fig. 1. General structure of direct command and control botnets

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Fig. 2. General structure of P2P-based botnets

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Fig. 3. Differences between DoS and DDoS

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Fig. 4. Blockchain technique schematization

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Fig. 5. schematization by attack stage

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Fig. 6. GPS data in picture files

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Fig. 7. Example of a simple EXIF metadata removal python program

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