• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.234-237
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• 2016

Address Resolution Protocol (ARP) is used for mapping a network address to physical address in many network technologies. However, since ARP protocol has no security feature, it always abused by attackers for performing ARP-based attacks. Researchers presented many technologies to improve ARP protocol, but most of them require a high implementation cost or scarify the network performance for using ARP protocol securely. In this paper, we present an ARP-disabled network system to neutralize the ARP-based attacks. "ARP-disabled" means suppress the ARP messages like request, response and broadcast messages, but not the ARP table. In our system, ARP tables are used for managing static ARP entries without prior knowledge (e.g. IP, MAC list of client devices). This is possible because the MAC address was designed to be derived from IP address. In general, our system is safe from the ARP-based attacks even the attacker has a strong power. Moreover, we saved network bandwidth by disabling the ARP messages.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.549-549
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• 2000

In the previous work, we dealt with a traffic analysis of network-based control system and its architecture using the CAN protocol. It is difficult to determine an optimal network architecture for a specific system. In this paper, we propose the architecture of network-based control system applicable to a specific AGV system with manipulator arms. We define the fixed number of periodic messages to be occurred in this system. In the proposed system architecture, we analyse its traffic for the real-time communication of all messages, determine the optimal sampling period of an analog sensor to be satisfied with the required specification and the number of possible sensors to be added through simulation.

• Journal of the Optical Society of Korea
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• v.11 no.3
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• pp.101-107
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• 2007

In this paper, we have presented the results of Wavelength Division Multiplexing-Passive Optical Network (WDM-PON) based fiber-to-the-home (FTTH) field trial test which was held in the city of Gwangju. We have implemented an injection locked Fabry-Perot Laser Diode (FP-LD) based WDM-PON system and reliably delivered Internet Protocol TV (IP-TV), networked Personal Video Recorder (N-PVR), High-Definition Video on Demand (HD-VoD), Education on Demand (EoD) and Internet service as FTTH service through the system during the field trial test. We have also verified that the WDM-PON system worked well to provide quality of service (QoS) guaranteed 100Mbps bandwidth per subscriber. Furthermore, we have presented network designing issues in Outside Plant (OSP) and Customer Premises Network (CPN) that should be overcome to efficiently deploy FTTH service. Finally, based on the field trial test results, we proposed FTTH service deployment strategies.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.35-42
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• 2019

In this paper, we propose an approach to apply network-based moving target defense into Internet of Things (IoT) networks. The IoT is a technology that provides the high interconnectivity of things like electronic devices. However, cyber security risks are expected to increase as the interconnectivity of such devices increases. One recent study demonstrated a man-in-the-middle attack in the statically configured IoT network. In recent years, a new approach to cyber security, called the moving target defense, has emerged as a potential solution to the challenge of static systems. The approach continuously changes system's attack surface to prevent attacks. After analyzing IPv4 / IPv6-based moving target defense schemes and IoT network-related technologies, we present our approach in terms of addressing systems, address mutation techniques, communication models, network configuration, and node mobility. In addition, we summarize the direction of future research in relation to the proposed approach.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.314-322
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• 2021

Skeleton-based action recognition has attracted considerable attention in human action recognition. Recent methods for skeleton-based action recognition employ spatiotemporal graph convolutional networks (GCNs) and have remarkable performance. However, most of them have heavy computational complexity for robust action recognition. To solve this problem, we propose a shuffle graph convolutional network (SGCN) which is a lightweight graph convolutional network using pointwise group convolution rather than pointwise convolution to reduce computational cost. Our SGCN is composed of spatial and temporal GCN. The spatial shuffle GCN contains pointwise group convolution and part shuffle module which enhances local and global information between correlated joints. In addition, the temporal shuffle GCN contains depthwise convolution to maintain a large receptive field. Our model achieves comparable performance with lowest computational cost and exceeds the performance of baseline at 0.3% and 1.2% on NTU RGB+D and NTU RGB+D 120 datasets, respectively.

• Smart Media Journal
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• v.12 no.11
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• pp.113-124
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• 2023

With the advent of 5G and B5G (Beyond 5G) networks, network virtualization technology that can overcome the limitations of existing networks is attracting attention. The purpose of network virtualization is to provide solutions for efficient network resource utilization and various services. Existing heuristic-based VNE (Virtual Network Embedding) techniques have been studied, but the flexibility is limited. Therefore, in this paper, we propose a GNN-based network slicing classification scheme to meet various service requirements and a RL-based VNE scheme for optimal resource allocation. The proposed method performs optimal VNE using an Actor-Critic network. Finally, to evaluate the performance of the proposed technique, we compare it with Node Rank, MCST-VNE, and GCN-VNE techniques. Through performance analysis, it was shown that the GNN and RL-based VNE techniques are better than the existing techniques in terms of acceptance rate and resource efficiency.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.409-412
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• 2007

Demand for the technology for access to device control network in industry and for access to building automation system via internet is on the increase. In such technology integration of a device control network with a data network such as internet and organizing wide-ranging DCS(distributed control system) is needed, and it can be realized in the framework of VDN(virtual device network). Specifications for device control network and data network are quite different because of the differences in application. So a router that translates the communication protocol between device control network and data network, and efficiently transmits information to destination is needed for implementation of the VDN(virtual device network). This paper proposes the concept of NCS(networked control system) based on VDN(virtual device network) and suggests the routing algorithm that uses embedded system.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.364-367
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• 2008

Many different types of network equipments are deployed in a large-scale IP network. In this operating environment, network service providers suffer from difficulty in controlling various equipments simultaneously in case network faults happen in their overall or regional network due to physical link failure or abnormal traffic. This paper presents a policy-based methodology to control many different types of network equipments at the same time in abnormal cases. The key idea is that NMS(Network Management System) keeps vendor-neutral control policies in normal times and that when an abnormal case occurs in network, NMS transforms the selected policy into vendor-specific control commands and enforces them to various equipments simultaneously.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.229-231
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• 2006

NLPCA(Nonlinear Principal Component Analysis) is a novel technique for multivariate data analysis, similar to the well-known method of principal component analysis. NLPCA operates by a feedforward neural network called AANN(Auto Associative Neural Network) which performs the identity mapping. In this work, a sensor fault detection system based on NLPCA is presented. To verify its applicability, simulation study on the data supplied from sensor network is executed.

• KIEE International Transactions on Electrophysics and Applications
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• v.3C no.4
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• pp.130-135
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• 2003

This study describes neural network based dissolved gas analysis using composition patterns of gas concentrations for transformer fault diagnosis. DGA samples were gathered from related literatures and classified into six types of faults and then a neural network was trained using the DGA samples. Diagnosis tests were performed by the trained neural network with DGA samples of serviced transformers, fault causes of which were identified by actual inspection. Diagnosis results by the neural network were in good agreement with actual faults.