DOI QR코드

DOI QR Code

프라이버시 침해 방지를 위한 얼굴 정보 변환 메커니즘

Face Information Conversion Mechanism to Prevent Privacy Infringement

  • 김진수 (강원대학교 대학원 정보통신공학전공.제주대학교 사이버보안인재교육원) ;
  • 김상춘 (강원대학교 정보통신공학전공) ;
  • 박남제 (제주대학교 초등교육학과)
  • 투고 : 2019.02.14
  • 심사 : 2019.05.03
  • 발행 : 2019.06.30

초록

CCTV(Closed-circuit Television)는 사고 예방 및 시설 안전을 위해 매년 설치대수가 증가함에 따라 1인당 CCTV에 노출되는 횟수가 증대되고 있으며, 노출되는 대상의 프라이버시 보호를 위해 지능형 영상감시 시스템 기술이 각광받고 있다. 지능형 영상감시 시스템은 촬영된 영상 데이터에 대한 단순한 식별에서 피사체의 행동 유형과 현장 상황 판단 등을 수행하거나, 촬영된 피사체의 정보가 노출될 수 있는 정보를 외부로 유출되지 않도록 프라이버시 보호를 위한 처리 과정을 진행한다. 제안된 기술은 영상감시 시스템에 적용되어 영상감시 시스템으로부터 촬영된 원본 영상 정보를 유사 영상 정보로 변환함으로서 외부에 원본 영상 정보가 유출되지 않도록 하는 기술이다. 본문에서는 미리 설정된 유사도에 근접하는 가상의 얼굴 이미지를 삽입하는 영상 변환메커니즘을 제안한다.

CCTV(Closed-Circuit Television) is increasingly exposed to CCTV per person as the number of installations increases every year for accident prevention and facility safety. The intelligent video surveillance system technology is attracting attention to the privacy protection of exposed subjects. The intelligent video surveillance system performs a process for the privacy protection so as to perform the action type of the subject and the judgment of the situation in the simple identification of the photographed image data, or to prevent the information, from which the information of the photographed subject is exposed. The proposed technique is applied to the video surveillance system and converts the original image information taken from the video surveillance system into similar image information so that the original image information is not leaked to the outside. In this paper, we propose an image conversion mechanism that inserts a virtual face image that approximates a preset similarity.

키워드

참고문헌

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  3. Blockchain Based Data-Preserving AI Learning Environment Model for Cyber Security System vol.17, pp.12, 2019, https://doi.org/10.14801/jkiit.2019.17.12.125
  4. Blockchain-Based Data-Preserving AI Learning Environment Model for AI Cybersecurity Systems in IoT Service Environments vol.10, pp.14, 2020, https://doi.org/10.3390/app10144718