인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
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
Safety and security are crucial for Connected and Automated Vehicles (CAVs), as they affect vehicle performance, passenger safety, and resilience to cyber threats. However, there is a gap in ensuring both safety and security, as they are often studied independently, causing existing safety mechanisms to weaken security mechanisms and vice versa. To address this gap, we propose an endogenous security and safety approach that employs dynamic heterogeneous redundancy (DHR) technologies. We first elaborate on the fundamental concept of integrated safety and security for CAVs, drawing upon the Vehicle-Road-Cloud ecosystem as well as the relevant design and development processes. Then, we design a dynamic heterogeneous redundancy-based integrated safety and security monitoring module, which is constructed around system kernel events. Empirical testing demonstrates the module maintain 100% system performance during failures and attacks through dynamic reconfiguration. Building upon this, we propose an in-depth defense solution for CAVs that combines mimicry defense, integrated safety and security monitoring, and dynamic reconfiguration. A prototype of this in-depth defense solution is implemented, followed by penetration testing to evaluate its practical effectiveness. Penetration testing across 122 vulnerability cases (including format strings and integer overflows) shows 95.9% defense success rate with 90% vulnerability coverage. Additionally, we identify the assessment of the proposed endogenous security and safety approach for CAVs, highlighting its lightweight design, robust safety and security, quantification capabilities, and tracing functions.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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