• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.186-201
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• 2021

As autonomous driving technology advances, the accuracy of the vehicle position is important for recognizing the environments around driving. Map-matching localization techniques based on high definition (HD) maps have been studied to improve localization accuracy. Because conventional map-matching techniques estimate the vehicle position based on an HD map reference dataset representing the center of the lane, the estimated position does not reflect the deviation of the lateral distance within the lane. Therefore, this paper proposes a localization system based on the reference lateral position dataset extracted using image processing and HD maps. Image processing extracts the driving lane number using inverse perspective mapping, multi-lane detection, and yellow central lane detection. The lane departure method estimates the lateral distance within the lane. To collect the lateral position reference dataset, this approach involves two processes: (i) the link and lane node is extracted based on the lane number obtained from image processing and position from GNSS/INS, and (ii) the lateral position is matched with the extracted link and lane node. Finally, the vehicle position is estimated by matching the GNSS/INS local trajectory and the reference lateral position dataset. The performance of the proposed method was evaluated by experiments carried out on a highway environment. It was confirmed that the proposed method improves accuracy by about 1.0m compared to GNSS / INS, and improves accuracy by about 0.04m~0.21m (7~30%) for each section when compared with the existing lane-level map matching method.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.6
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• pp.13-25
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• 2005

In these days, there are various uses of Linux such as small embedded systems, routers, and huge servers, because Linux gives several advantages to system developers by allowing to use the open source code of the Linux kernel. On the other hand, the open source nature of the Linux kernel gives a bad influence on system security. If someone wants to exploit Linux-based systems, the attacker can easily do it by finding vulnerabilities of their Linux kernel sources. There are many kinds of existing methods for lading source-level vulnerabilities of softwares, but they are not suitable for finding source-level vulnerabilities of the Linux kernel which has an enormous amount of source code. In this paper, we propose the Onion mechanism as a methodology of finding source-level vulnerabilities of Linux kernel variables. The Onion mechanism is made up of two steps. The Int step is to select variables that may be vulnerable by using pattern matching mechanism and the second step is to inspect vulnerability of each selected variable by constructing and analyzing the system call trees. We also evaluate our proposed methodology by applying it to two well-known source-level vulnerabilities.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.1
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• pp.31-49
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• 2021

IoT devices refer to embedded devices that can communicate with networks. Since there are various types of IoT devices and they are widely used around us, in the event of an attack, damages such as personal information leakage can occur depending on the type of device. While the security team analyzes IoT devices, they should target firmware as well as software interfaces since IoT devices are operated by both of them. However, the problem is that it is not easy to extract and analyze firmware and that it is not easy to manage product quality at a certain level even if the same target is analyzed according to the analyst's expertise within the security team. Therefore, in this paper, we intend to establish a vulnerability analysis process for the firmware of IoT devices and present available tools for each step. Besides, we organized the process from firmware acquisition to analysis of IoT devices produced by various commercial manufacturers, and we wanted to prove their validity by applying it directly to drone analysis by various manufacturers.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.73-82
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• 2009

Due to the many advantages including low price, low power consumption, and miniaturization, the CMOS camera has been utilized in many applications, including mobile phones, the automotive industry, medical sciences and sensoring, robotic controls, and research in the security field. In particular, the 360 degree omni-directional camera when utilized in multi-camera applications has displayed issues of software nature, interface communication management, delays, and a complicated image display control. Other issues include energy management problems, and miniaturization of a multi-camera in the hardware field. Traditional CMOS camera systems are comprised of an embedded system that consists of a high-performance MCU enabling a camera to send and receive images and a multi-layer system similar to an individual control system that consists of the camera's high performance Micro Controller Unit. We proposed the SL-AVS (Small Size/Low power Around-View System) to be able to control a camera while collecting image data using a high speed synchronization technique on the foundation of a single layer low performance MCU. It is an initial model of the omni-directional camera that takes images from a 360 view drawing from several CMOS camera utilizing a 110 degree view. We then connected a single MCU with four low-power CMOS cameras and implemented controls that include synchronization, controlling, and transmit/receive functions of individual camera compared with the traditional system. The synchronization of the respective cameras were controlled and then memorized by handling each interrupt through the MCU. We were able to improve the efficiency of data transmission that minimizes re-synchronization amongst a target, the CMOS camera, and the MCU. Further, depending on the choice of users, respective or groups of images divided into 4 domains were then provided with a target. We finally analyzed and compared the performance of the developed camera system including the synchronization and time of data transfer and image data loss, etc.