인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
개인구독
소속 기관이 없으신 경우, 개인 정기구독을 하시면 저렴하게
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지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
This paper reports on a detection technique for stealthy sensor attacks on cyber-physical systems (CPS). The considered attack is a pole-dynamics attack, in which false data are injected to cancel the unstable trajectory of a plant captured on the feedback sensor output. In this attack, the systems appear to operate normally in the steady-state while the plant is destabilized. The target system is a linear plant, including unstable pole-dynamics, and we assume that the adversary knows the model to carry out the attack. The proposed detection method employs a switching mechanism of two control modes that play different roles. The first mode is the normal mode, which consists of a linear controller and an anomaly detector, having the same structure as those used in conventional networked control systems. The second mode is the attack detection mode, which utilizes an internal feedback controller. It is assumed that this internal controller is not known to the adversary. When the system is in the attack detection mode, owing to the use of the internal controller, the overall system dynamics differ from those adopted by the adversary, thereby the effect of the attack is revealed. The CPS periodically switches between the attack detection mode and normal mode. The timing of the switch is determined to ensure that any attack is revealed before the physical system becomes unstable. The results are validated via simulations of quadrotor control.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
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UCI(KEPA) : I410-ECN-0101-2021-003-001475062