• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.580-599
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• 2021

Software-Defined Networking (SDN) has three key features: separation of control and forwarding, centralized control, and network programmability. While improving network management flexibility, SDN has many security issues. This paper systemizes the security threats of SDN using spoofing, tampering, repudiation, information disclosure, denial of service, and elevation of privilege (STRIDE) model to understand the current security status of SDN. First, we introduce the network architecture and data flow of SDN. Second, we analyze security threats of the six types given in the STRIDE model, aiming to reveal the vulnerability mechanisms and assess the attack surface. Then, we briefly describe the corresponding defense technologies. Finally, we summarize the work of this paper and discuss the trends of SDN security research.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.269-282
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• 2023

The purpose of this study was to construct land cover maps using a deep learning model and to select the optimal deep learning model for land cover classification by adjusting the dataset such as input image size and Stride application. Two types of deep learning models, the U-net model and the DeeplabV3+ model with an Encoder-Decoder network, were utilized. Also, the combination of the two deep learning models, which is an Ensemble model, was used in this study. The dataset utilized RapidEye satellite images as input images and the label images used Raster images based on the six categories of the land use of Intergovernmental Panel on Climate Change as true value. This study focused on the problem of the quality improvement of the dataset to enhance the accuracy of deep learning model and constructed twelve land cover maps using the combination of three deep learning models (U-net, DeeplabV3+, and Ensemble), two input image sizes (64 × 64 pixel and 256 × 256 pixel), and two Stride application rates (50% and 100%). The evaluation of the accuracy of the label images and the deep learning-based land cover maps showed that the U-net and DeeplabV3+ models had high accuracy, with overall accuracy values of approximately 87.9% and 89.8%, and kappa coefficients of over 72%. In addition, applying the Ensemble and Stride to the deep learning models resulted in a maximum increase of approximately 3% in accuracy and an improvement in the issue of boundary inconsistency, which is a problem associated with Semantic Segmentation based deep learning models.

• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.27-37
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• 2022

Virtual private network (VPN) services are used in various environments related to national security, such as defense companies and defense-related institutions where digital communication environment technologies are diversified and access to network use is increasing. However, the number of cyber attacks that target vulnerable points of the VPN has annually increased through technological advancement. Thus, this study identified security requirements by performing STRIDE threat modeling to prevent potential and new vulnerable points that can occur in the VPN. STRIDE threat modeling classifies threats into six categories to systematically identify threats. To apply the proposed security requirements, this study analyzed functions of the VPN and formed a data flow diagram in the VPN service process. Then, it collected threats that can take place in the VPN and analyzed the STRIDE threat model based on data of the collected threats. The data flow diagram in the VPN service process, which was established by this study, included 96 STRIDE threats. This study formed a threat scenario to analyze attack routes of the classified threats and derived 30 security requirements for each element of the VPN based on the formed scenario. This study has significance in that it presented a security guideline for enhancing security stability of the VPN used in facilities that require high-level security, such as the Ministry of National Defense (MND).

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.989-992
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• 2004

In general, it is known that walking stability of a quadruped is determined by its COG(Center of Gravity). In this paper, in order to know whether our virtual quadruped robot is applicable to the real quadruped robot, we simulated our virtual model using the data from the real robot‘s walking. We were able to evaluate the stride of quadruped based on direct and inverse kinematics and compared the stride of the simulation with real robot’s it. During the simulation we calculated the COG of the virtual model and evaluated the walking stability of real model.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.6
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• pp.221-227
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• 2002

In this paper, the system model for the compensation of the low-cost personal navigation system is derived and the error compensation method using GPS is also proposed. WNS(Walking Navigation System) is a kind of personal navigation system using the number of a walk, stride and azimuth. Because the accuracy of these variables determines the navigation performance, computational methods have been investigated. The step is detected using the walking patterns, stride is determined by neural network and azimuth is calculated with gyro output. The neural network filters off unnecessary motions. However, the error compensation method is needed, because the error of navigation information increases with time. In this paper, the accumulated error due to the step detection error, stride error and gyro bias is compensated by the integrating with GPS. Loosely coupled Kalman filter is used for the integration of WNS and GPS. It is shown by simulation that the error is bounded even though GPS signal is blocked.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1257-1262
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• 2018

In this paper, a deep learning method is proposed to detect the fire effectively by using video of surveillance camera. Based on AlexNet model, classification performance is compared according to kernel size and stride of convolution layer. Dataset for learning and interfering are classified into two classes such as normal and fire. Normal images include clouds, and foggy images, and fire images include smoke and flames images, respectively. As results of simulations, it is shown that the larger kernel size and smaller stride shows better performance.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.215-219
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• 2003

In this paper, we generate a trajectory minimized the energy gait of a biped robot for walking a staircase using genetic algorithms and apply to the computed torque controller for the stable dynamic biped locomotion. In the saggital plane, a 6 degree of freedom biped robot that model consists of seven links is used. In order to minimize the total energy efficiency, the Real-Coded Genetic Algorithm (RCGA) is used. Operators of genetic algorithms are composed of a reproduction, crossover and mutation. In order to approximate the walking gait, the each joint angle is defined as a 4-th order polynomial of which coefficients are chromosomes. Constraints are divided into equality and inequality. Firstly, equality constraints consist of position conditions at the end of stride period and each joint angle and angular velocity condition for periodic walking. On the other hand, inequality constraints include the knee joint conditions, the zero moment point conditions for the x-direction and the tip conditions of swing leg during the period of a stride for walking a staircase.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.114.5-114
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• 2001

In this paper, the model for personal navigation system using low-cost inertial sensors and error compensation method with GPS are proposed. Simulation is accomplished for the performance test. WNS(Walking Navigation System) is a kind of personal navigation using the number of a walk, stride and azimuth. Because the accuracy of these variables determines the navigational performance, computational methods have been investigated. The step is detected using the motion pattern by walking motion, stride is determined by neural network and azimuth is calculated with gyro´s output. The neural network filters off unnecessary motions. However, error compensation method is needed, because the error of navigation information increases with time ...

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.1
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• pp.229-239
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• 2018

This paper analyzes the problems of existing CCTV and discusses cyber security problems of IP-CCTV in cloud computing environment. In order to reduce the risk of simply removing the risk associated with the provision of cloud services, the risk analysis and counter-measures need to be carried out effectively. Therefore, the STRIDE model as the Threat Risk Modeling is used to analyze the risk factors, and Analytic Hierarchy Process(AHP) is used to measure risk priorities based on the analyzed threats.

• Journal of the Korea Convergence Society
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• v.6 no.5
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• pp.33-38
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• 2015

In a V2X convergence service environment, the principal service among infotainment services and driver management services must be supported centering on critical information of the driver, maintenance manager, customer, and anonymous user. Many software applications have considered solutions to be satisfied the specific requirements of driving care programs, and plans. This paper describes data flow diagram of a secure clinic system for driving car diagnosis, which is included in clinic configuration, clinic, clinic page, membership, clinic request processing, driver profile data, clinic membership data, and clinic authentication in the V2X convergence service environment. It is reviewed focusing on security threat issue of ITS diagnostic system such as spoofing, tampering, repudiation, disclosure, denial of service, and privilege out of STRIDE model.