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An Efficient ECU Analysis Technology through Non-Random CAN Fuzzing (Non-Random CAN Fuzzing을 통한 효율적인 ECU 분석 기술)

  • Kim, Hyunghoon;Jeong, Yeonseon;Choi, Wonsuk;Jo, Hyo Jin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.30 no.6
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    • pp.1115-1130
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    • 2020
  • Modern vehicles are equipped with a number of ECUs(Electronic Control Units), and ECUs can control vehicles efficiently by communicating each other through CAN(Controller Area Network). However, CAN bus is known to be vulnerable to cyber attacks because of the lack of message authentication and message encryption, and access control. To find these security issues related to vehicle hacking, CAN Fuzzing methods, that analyze the vulnerabilities of ECUs, have been studied. In the existing CAN Fuzzing methods, fuzzing inputs are randomly generated without considering the structure of CAN messages transmitted by ECUs, which results in the non-negligible fuzzing time. In addition, the existing fuzzing solutions have limitations in how to monitor fuzzing results. To deal with the limitations of CAN Fuzzing, in this paper, we propose a Non-Random CAN Fuzzing, which consider the structure of CAN messages and systematically generates fuzzing input values that can cause malfunctions to ECUs. The proposed Non-Random CAN Fuzzing takes less time than the existing CAN Fuzzing solutions, so it can quickly find CAN messages related to malfunctions of ECUs that could be originated from SW implementation errors or CAN DBC(Database CAN) design errors. We evaluated the performance of Non-Random CAN Fuzzing by conducting an experiment in a real vehicle, and proved that the proposed method can find CAN messages related to malfunctions faster than the existing fuzzing solutions.

Development of an X3D Python Language Binding Viewer Providing a 3D Data Interface (3D 데이터 인터페이스를 제공하는 X3D Python 언어 바인딩 뷰어 개발)

  • Kim, Ha Seong;Lee, Myeong Won
    • KIPS Transactions on Software and Data Engineering
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    • v.10 no.6
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    • pp.243-250
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    • 2021
  • With the increased development of 3D VR applications augmented by recent VR/AR/MR technologies and by the advance of 3D devices, interchangeability and portability of 3D data have become essential. 3D files should be processed in a standard data format for common usage between applications. Providing standardized libraries and data structures along with the standard file format means that a more efficient system organization is possible and unnecessary processing due to the usage of different file formats and data structures depending on the applications can be omitted. In order to provide the function of using a common data file and data structure, this research is intended to provide a programming binding tool for generating and storing standardized data so that various services can be developed by accessing the common 3D files. To achieve this, this paper defines a common data structure including classes and functions to access X3D files with a standardized scheme using the Python programming language. It describes the implementation of a Python language binding viewer, which is an X3D VR viewer for rendering standard X3D data files based on the language binding interface. The VR viewer includes Python based 3D scene libraries and a data structure for creation, modification, exchange, and transfer of X3D objects. In addition, the viewer displays X3D objects and processes events using the libraries and data structure.

Development of CanSat System for Collecting Weather Information With Autorotating Science Payload Ejection Function (자동회전 과학 탑재체 사출 기능을 갖춘 기상정보 수집용 캔위성 체계 개발)

  • Kim, Youngjun;Park, Junsoo;Nam, Jaeyoung;Lee, Junhyuck;Choi, Yunwon;Yoo, Seunghoon;Lee, Sanghyun;Lee, Younggun
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.50 no.8
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    • pp.573-581
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    • 2022
  • This paper deals with the development of CanSat system, which ejects two maple seed-type autorotating science payloads and collects weather information. The CanSat consists of two autorotating science payloads and a container. The container is equipped with devices for launching science payloads and communication with the ground station, and launches science payloads one by one at different designated altitudes. The science payload consists of a space for loading and a large wing, and rotates to generate lift for slowing down the fall speed. Specifically, after being ejected, it descends at a speed of 20 m/s or less, measures the rotation rate, atmospheric pressure, and temperature, and transmits the measured value to the container at a rate of once per second. The communication system is a master-slave structure, and the science payload transmits all data to the master container, which aggregates both the received data and its own data, and transmits it to the ground station. All telemetry can be checked in real time using the ground station software developed in-house. A simulation was performed in the simulation environment, and the performance of the CanSat system that satisfies the mission requirements was confirmed.

DNN-Based Dynamic Cell Selection and Transmit Power Allocation Scheme for Energy Efficiency Heterogeneous Mobile Communication Networks (이기종 이동통신 네트워크에서 에너지 효율화를 위한 DNN 기반 동적 셀 선택과 송신 전력 할당 기법)

  • Kim, Donghyeon;Lee, In-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.10
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    • pp.1517-1524
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    • 2022
  • In this paper, we consider a heterogeneous network (HetNet) consisting of one macro base station and multiple small base stations, and assume the coordinated multi-point transmission between the base stations. In addition, we assume that the channel between the base station and the user consists of path loss and Rayleigh fading. Under these assumptions, we present the energy efficiency (EE) achievable by the user for a given base station and we formulate an optimization problem of dynamic cell selection and transmit power allocation to maximize the total EE of the HetNet. In this paper, we propose an unsupervised deep learning method to solve the optimization problem. The proposed deep learning-based scheme can provide high EE while having low complexity compared to the conventional iterative convergence methods. Through the simulation, we show that the proposed dynamic cell selection scheme provides higher EE performance than the maximum signal-to-interference-plus-noise ratio scheme and the Lagrangian dual decomposition scheme, and the proposed transmit power allocation scheme provides the similar performance to the trust region interior point method which can achieve the maximum EE.

Implementation of Real-time Sedentary Posture Correction Cushion Using Capacitive Pressure Sensor Based on Conductive Textile

  • Kim, HoonKi;Park, HyungSoo;Oh, JiWon
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.2
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    • pp.153-161
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    • 2022
  • Physical activities are decreasing and sitting time is increasing due to the automation, smartization, and intelligence of necessary household items throughout daily life. Recent healthcare studies have reported that the likelihood of obesity, diabetes, cardiovascular disease, and early death increases in proportion to sitting time. In this paper, we develop a sitting posture correction cushion in real time using capacitive pressure sensor based on conductive textile. It develops a pressure sensor using conductive textile, a key component of the posture correction cushion, and develops a low power-based pressure measurement circuit. It provides a function to transmit sensor values measured in real time to smartphones using BLE short-range wireless communication on the posture correction cushion, and develops a mobile application to check the condition of the sitting posture through these sensor values. In the mobile app, you can visualize your sitting posture and check it in real time, and if you keep it in the wrong posture for a certain period of time, you can notify it through an alarm. In addition, it is possible to visualize the sitting time and posture accuracy in a graph. Through the correction cushion in this paper, we experiment with how effective it is to correct the user's posture by recognizing the user's sitting posture, and present differentiation and excellence compared to other product.

Efficient CT Image Denoising Using Deformable Convolutional AutoEncoder Model

  • Eon Seung, Seong;Seong Hyun, Han;Ji Hye, Heo;Dong Hoon, Lim
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.3
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    • pp.25-33
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    • 2023
  • Noise generated during the acquisition and transmission of CT images acts as a factor that degrades image quality. Therefore, noise removal to solve this problem is an important preprocessing process in image processing. In this paper, we remove noise by using a deformable convolutional autoencoder (DeCAE) model in which deformable convolution operation is applied instead of the existing convolution operation in the convolutional autoencoder (CAE) model of deep learning. Here, the deformable convolution operation can extract features of an image in a more flexible area than the conventional convolution operation. The proposed DeCAE model has the same encoder-decoder structure as the existing CAE model, but the encoder is composed of deformable convolutional layers and the decoder is composed of conventional convolutional layers for efficient noise removal. To evaluate the performance of the DeCAE model proposed in this paper, experiments were conducted on CT images corrupted by various noises, that is, Gaussian noise, impulse noise, and Poisson noise. As a result of the performance experiment, the DeCAE model has more qualitative and quantitative measures than the traditional filters, that is, the Mean filter, Median filter, Bilateral filter and NL-means method, as well as the existing CAE models, that is, MAE (Mean Absolute Error), PSNR (Peak Signal-to-Noise Ratio) and SSIM. (Structural Similarity Index Measure) showed excellent results.

Evaluation of Compaction Quality Control applied the Dynamic Cone Penetrometer Test based on IoT (다짐품질관리를 위한 IoT 기반 DCPT 적용 평가)

  • Jisun, Kim;Jinyoung, Kim;Namgyu, Kim;Sungha, Baek;Jinwoo, Cho
    • Journal of the Korean Geosynthetics Society
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    • v.21 no.4
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    • pp.1-12
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    • 2022
  • Generally, the plate load test and the field density test are conducted for compaction quality control in earthwork, and then additional analysis. Recently developed that the DCPT (Dynamic Cone Penetration Test) equipment for smart compaction quality control its the system are able to get location and real-time information about worker history management. The IoT-based the DCPT system improved the time-cost in the field compared traditional test, and the functions recording and storage of the DPI (Dynamic Cone Penetration Index) were automated. This paper describes using these DCPT equipment on in-situ and compared to the standards of the DCPT, and the compaction trend had be confirmed with DPI as the field test data. As a result, the DPI of the final compaction decreased by 1.4 times compared to the initial compaction, confirming the increase in the compaction strength of the subgrade compaction layer 10 to 14 cm deep from the surface. A trend of increasing compaction strength was observed. This showed a tendency to increase the compaction strength of the target DPI proposed by MnDOT and the results of the existing plate load test, but there was a difference in the increase rate. Therefore, additional studies are needed on domestic compaction materials and laboratory conditions for target DPI and correlation studies with the plate load tests. If this is reflected, it is suggested that DCPT will be widely used as smart construction equipment in earthworks.

Digital Twin-Based Communication Optimization Method for Mission Validation of Swarm Robot (군집 로봇의 임무 검증 지원을 위한 디지털 트윈 기반 통신 최적화 기법)

  • Gwanhyeok, Kim;Hanjin, Kim;Junhyung, Kwon;Beomsu, Ha;Seok Haeng, Huh;Jee Hoon, Koo;Ho Jung, Sohn;Won-Tae, Kim
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.1
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    • pp.9-16
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    • 2023
  • Robots are expected to expand their scope of application to the military field and take on important missions such as surveillance and enemy detection in the coming future warfare. Swarm robots can perform tasks that are difficult or time-consuming for a single robot to be performed more efficiently due to the advantage of having multiple robots. Swarm robots require mutual recognition and collaboration. So they send and receive vast amounts of data, making it increasingly difficult to verify SW. Hardware-in-the-loop simulation used to increase the reliability of mission verification enables SW verification of complex swarm robots, but the amount of verification data exchanged between the HILS device and the simulator increases exponentially according to the number of systems to be verified. So communication overload may occur. In this paper, we propose a digital twin-based communication optimization technique to solve the communication overload problem that occurs in mission verification of swarm robots. Under the proposed Digital Twin based Multi HILS Framework, Network DT can efficiently allocate network resources to each robot according to the mission scenario through the Network Controller algorithm, and can satisfy all sensor generation rates required by individual robots participating in the group. In addition, as a result of an experiment on packet loss rate, it was possible to reduce the packet loss rate from 15.7% to 0.2%.

Designing a Blockchain-based Smart Contract for Seafarer Wage Payment (블록체인 기반 선원 임금지불을 위한 스마트 컨트랙트 설계)

  • Yoo, Sang-Lok;Kim, Kwang-Il;Ahn, Jang-Young
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.27 no.7
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    • pp.1038-1043
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    • 2021
  • Guaranteed seafarer wage payment is essential to ensure a stable supply of seafarers. However, disputes over non-payment of wages to seafarers often occur. In this study, an automatic wage payment system was designed using a blockchain-based smart contract to resolve the problem of seafarers' wage arrears. The designed system consists of an information register, a matching processing unit, a review rating management unit, and wage remittance before deploying smart contracts. The matching process was designed to send an automatic notification to seafarers and shipowners if the sum of the weight of the four variables, namely wages, ship type/fishery, position, and license, exceeded a pre-defined threshold. In addition, a review rating management system, based on a combination of mean and median, was presented to serve as a medium to mutually fulfill the normal working conditions. The smart contract automatically fulfills the labor contract between the parties without an intermediary. This system will naturally resolve problems such as fraudulent advance payment to seafarers, embezzlement by unregistered employment agencies, overdue wages, and forgery of seafarers' books. If this system design is commercialized and institutionally activated, it is expected that stable wages will be guaranteed to seafarers, and in turn, the difficulties in human resources supply will be solved. We plan to test it in a local environment for further developing this system.

An Efficient Routing Scheme based on Link Quality and Load Balancing for Wireless Sensor Networks (무선 센서 네트워크에서 링크 상태 및 트래픽 분산 정보를 이용한 효과적인 라우팅 방법)

  • Kim, Sun-Myeng;Yang, Yeon-Mo
    • Journal of the Korea Society for Simulation
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    • v.19 no.4
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    • pp.11-19
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    • 2010
  • ZigBee is a standard for wireless personal area networks(WPANs) based on the IEEE 802.15.4 standard. It has been developed for low cost and low power consumption. There are two alternative routing schemes that have been proposed for the ZigBee standard: Ad-hoc On-Demand Distance Vector(AODV) and tree routing. The tree routing forwards packets from sensors to a sink node based on the parent-child relationships established by the IEEE 802.15.4 MAC topology formation procedure. In order to join the network, a sensor node chooses an existing node with the strongest RSSI(Received signal strength indicator) signal as a parent node. Therefore, some nodes carry a large amount of traffic load and exhaust their energy rapidly. To overcome this problem, we introduce a new metric based on link quality and traffic load for load balancing. Instead of the strength of RSSI, the proposed scheme uses the new metric to choose a parent node during the topology formation procedure. Extensive simulation results using TOSSIM(TinyOS mote SIMulator) show that the CFR scheme outperforms well in comparison to the conventional tree routing scheme.