지능형 예측감시 시스템을 위한 보안 프레임워크
Security Framework for Intelligent Predictive Surveillance Systems
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초록
최근 지능형 예측감시 시스템이 등장하고 있다. 지능형 예측감시 시스템의 추론을 위해서는 현재 및 과거의 데이터가 필요하며, 이러한 데이터의 분석을 통하여 곧 발생할 상황에 대한 예측을 가능하게 한다. 그러나, 이러한 과정에서 영상 객체의 개인정보를 취급하게 될 소지가 높으므로, 개인정보보호를 위해서는 보안에 대한 고려가 필수적이다. 특히, 개인의 생활패턴, 주요 이동 경로 등에 대한 정보가 해킹을 통하여 공개적으로 노출된다면 프라이버시 측면에서 문제가 될 것이다. 기존의 영상감시 프레임워크는 개인정보보호 측면에서 한계점이 있으며, 특히 개인정보보호에 취약한 측면이 있다. 본 논문에서는 개인정보보호를 고려한 지능형 예측감시 시스템을 위한 보안 프레임워크를 제안하였다. 제안한 방법에서는 단말, 전송, 감시, 모니터링 계층으로 구분하여 단위별 세부 구성요소를 명시하였으며, 특히 객체 단위별 세부 접근제어와 비식별화를 지원하여 영상감시 과정에서의 능동형 개인정보보호가 가능하다. 또한, 데이터 전송시 보안 기능과 RBAC 제공을 통한 접근제어의 장점을 갖는다.
Abstract
Recently, intelligent predictive surveillance system has emerged. It is a system that can probabilistically predict the future situation and event based on the existing data beyond the scope of the current object or object motion and situation recognition. Since such intelligent predictive monitoring system has a high possibility of handling personal information, security consideration is essential for protecting personal information. The existing video surveillance framework has limitations in terms of privacy. In this paper, we proposed a security framework for intelligent predictive surveillance system. In the proposed method, detailed components for each unit are specified by dividing them into terminals, transmission, monitoring, and monitoring layers. In particular, it supports active personal information protection in the video surveillance process by supporting detailed access control and de-identification.
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