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.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2023.11
- 수록면
- 1,384 - 1,389 (6page)
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초록· 키워드
오류제보하기
The advancement of autonomous driving technology plays a pivotal role in transforming the driving environment and enhancing the efficiency and convenience of vehicle operation. However, autonomous driving systems are composed of various Electronic Control Units (ECUs) connected through networks, making them susceptible to security attacks such as hacking. These attacks can lead to severe consequences, including system manipulation and personal data breaches, highlighting the critical issue of security.
As a result, evaluating the security of autonomous driving systems is of utmost importance. Security evaluation involves thorough validation of various attack scenarios and threat models for ECUs to identify potential vulnerabilities and weaknesses. To achieve this, our research leverages Hardware-in-the-Loop (HIL) simulation and the Controller Area Network (CAN) Fuzzer technique.
HIL simulation is a robust method that combines real hardware and software components to conduct experiments under conditions closely resembling actual operating environments. In this study, we establish an HIL simulation environment to simulate the interaction between an autonomous driving logic-equipped vehicle model and ECUs. The CAN Fuzzer is a tool that transmits massive input data to ECUs via the CAN communication protocol, generated randomly. Such input data is employed for modeling unexpected and attack scenarios. Fuzzer, in conjunction with the connected CAN bus network, evaluates how ECUs respond to attacks.
The primary objective of this study is to develop a methodology for assessing the security of autonomous driving ECUs by combining HIL simulation and the CAN Fuzzer technique. This methodology encompasses the detection of potential security vulnerabilities and the assessment of exploitability, among various factors, including emergency response calculation.
Therefore, in this paper, we conduct research involving HIL simulation to test the system"s response in various situations of autonomous vehicles and employ CAN Fuzzer to identify ECU vulnerabilities in the development of a security evaluation methodology
As a result, evaluating the security of autonomous driving systems is of utmost importance. Security evaluation involves thorough validation of various attack scenarios and threat models for ECUs to identify potential vulnerabilities and weaknesses. To achieve this, our research leverages Hardware-in-the-Loop (HIL) simulation and the Controller Area Network (CAN) Fuzzer technique.
HIL simulation is a robust method that combines real hardware and software components to conduct experiments under conditions closely resembling actual operating environments. In this study, we establish an HIL simulation environment to simulate the interaction between an autonomous driving logic-equipped vehicle model and ECUs. The CAN Fuzzer is a tool that transmits massive input data to ECUs via the CAN communication protocol, generated randomly. Such input data is employed for modeling unexpected and attack scenarios. Fuzzer, in conjunction with the connected CAN bus network, evaluates how ECUs respond to attacks.
The primary objective of this study is to develop a methodology for assessing the security of autonomous driving ECUs by combining HIL simulation and the CAN Fuzzer technique. This methodology encompasses the detection of potential security vulnerabilities and the assessment of exploitability, among various factors, including emergency response calculation.
Therefore, in this paper, we conduct research involving HIL simulation to test the system"s response in various situations of autonomous vehicles and employ CAN Fuzzer to identify ECU vulnerabilities in the development of a security evaluation methodology
#HIL(Hardware-In-the-Loop)
#Fuzzing Test(퍼징 테스트)
#ECU(Electronic Control unit, 전자 제어 유닛)
#HS CAN(High Speed Controller Area Network)
#CAN FD(Controller Area Network Flexible Data-Rate)
#Vehicle network security(차량네트워크보안)
#OSM(Open Street MAP,오픈소스지도서비스)
#AEB(Autonomous Emergency Braking, 자동긴급제동장치)
#ACC(adaptive cruise control, 어댑티브 크루즈 컨트롤)
#BSD(Blind Spot Assist, 사각지대 경보장치)
목차
Abstract
1. 서론
2. HILS 평가 환경 개발
3. ECU HIL 시뮬레이션
4. ECU 보안성 평가
5. 결론
References
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