• Title/Summary/Keyword: Vehicle Safety Communication

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Security Credential Management & Pilot Policy of U.S. Government in Intelligent Transport Environment (지능형 교통 환경에서 미국정부의 보안인증관리 & Pilot 정책)

  • Hong, Jin-Keun
    • Journal of Convergence for Information Technology
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    • v.9 no.9
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    • pp.13-19
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    • 2019
  • This paper analyzed the SCMS and pilot policy, which is pursued by the U.S. government in connected vehicles. SCMS ensures authentication, integrity, privacy and interoperability. The SCMS Support Committee of U.S. government has established the National Unit SCMS and is responsible for system-wide control. Of course, it introduces security policy, procedures and training programs making. In this paper, the need for SCMS to be applied to C-ITS was discussed. The structure of the SCMS was analyzed and the U.S. government's filot policy for connected vehicles was discussed. The discussion of the need for SCMS highlighted the importance of the role and responsibilities of SCMS between vehicles and vehicles. The security certificate management system looked at the structure and analyzed the type of certificate used in the vehicle or road side unit (RSU). The functions and characteristics of the certificates were reviewed. In addition, the functions of basic safety messages were analyzed with consideration of the detection and warning functions of abnormal behavior in SCMS. Finally, the status of the pilot project for connected vehicles currently being pursued by the U.S. government was analyzed. In addition to the environment used for the test, the relevant messages were also discussed. We also looked at some of the issues that arise in the course of the pilot project.

Unsupervised Learning-Based Threat Detection System Using Radio Frequency Signal Characteristic Data (무선 주파수 신호 특성 데이터를 사용한 비지도 학습 기반의 위협 탐지 시스템)

  • Dae-kyeong Park;Woo-jin Lee;Byeong-jin Kim;Jae-yeon Lee
    • Journal of Internet Computing and Services
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    • v.25 no.1
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    • pp.147-155
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    • 2024
  • Currently, the 4th Industrial Revolution, like other revolutions, is bringing great change and new life to humanity, and in particular, the demand for and use of drones, which can be applied by combining various technologies such as big data, artificial intelligence, and information and communications technology, is increasing. Recently, it has been widely used to carry out dangerous military operations and missions, such as the Russia-Ukraine war and North Korea's reconnaissance against South Korea, and as the demand for and use of drones increases, concerns about the safety and security of drones are growing. Currently, a variety of research is being conducted, such as detection of wireless communication abnormalities and sensor data abnormalities related to drones, but research on real-time detection of threats using radio frequency characteristic data is insufficient. Therefore, in this paper, we conduct a study to determine whether the characteristic data is normal or abnormal signal data by collecting radio frequency signal characteristic data generated while the drone communicates with the ground control system while performing a mission in a HITL(Hardware In The Loop) simulation environment similar to the real environment. proceeded. In addition, we propose an unsupervised learning-based threat detection system and optimal threshold that can detect threat signals in real time while a drone is performing a mission.