무인이동체 이상행위 탐지를 위한 소프트웨어 정의형 테스트베드 설계 및 구현
Design and Implementation of Software Defined Testbed for UAV Abnormality Detection
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초록
무인이동체 시스템은 운용 과정에서 다양한 하드웨어 및 소프트웨어 구성요소를 복합적으로 사용한다. 이처럼 다양한 구성요소가 결합 되어 동작하는 무인이동체 시스템은 각 구성요소에 대한 다양한 결함 및 보안 위협에 노출되어 있다. 이에 따라 무인이동체의 일부 위험 및 위협 요소를 대상으로 무인이동체의 이상행위를 탐지하기 위한 다양한 연구들이 꾸준히 수행되어왔다. 무인이동체의 다양한 위험 및 위협 요소를 고려했을 때 실질적인 무인이동체 운용환경에서 이상행위 탐지 알고리즘의 신뢰성 있는 도입을 위해, 이상행위를 유발하는 각각의 요소에 대한 탐지 커버리지를 확장하여 무인이동체 시스템 전반의 강건성 및 보안성을 향상할 필요가 있다. 하지만 기존 이상행위 탐지 알고리즘의 통합적 도입과 검증 과정에서, 각 알고리즘이 이상행위 탐지를 위해 사용하는 데이터의 차이로 인한 통합의 어려움이 있다. 따라서 본 논문은 다양한 이상행위의 요인의 다각적인 수집 및 행위 결과에 대한 분석이 가능한 소프트웨어 정의형 무인이동체 테스트베드의 설계 및 구현을 통해 이상행위 탐지 개발과 적용 및 검증에서의 활용성을 높이고자 한다.
Abstract
The UAV(Unmanned Aerial vehicle) system uses a variety of hardware and software components in the process of operation. The UAV system operating in combination with various components is exposed to various defects and security threats for each component. Accordingly, various studies for detecting abnormal behavior of the UAV system have been continuously studied for some risks and threats of the UAV system. Thus, considering the various defeats and threats of the UAV system, it is necessary to reliably introduce the anomaly detection algorithm in a practical unmanned mobile operating environment. In addition, it is necessary to improve the robustness and security of the overall UAV system by extending the detection coverage for each element that causes abnormal behavior. However, in the process of integrating and verifying the existing anomaly detection algorithm, there is a difficulty in integration due to differences in data used by each algorithm. Therefore, we design and implement a software-defined UAV testbed capable of multi-faceted collection of variables that can be a factor of various abnormal behaviors and analysis of UAV behavior results. Through this, we intend to increase the usability in the development, application and verification of abnormal behavior detection.
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- "ardupilot"[URL]
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