• KIPS Transactions on Computer and Communication Systems
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• v.1 no.2
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• pp.109-118
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• 2012

As a result of the prevalence of smartphone, various mobile services became faster by LTE networks. Because many mobile devices are used more wireless services, heavy signaling traffic for authentication could be generated. Authentication is an important factor in wireless networks to identify devices; it is the start of wireless networks. This paper analyzes previous patterns for more effective authentication in accessing of another external networks. We propose a fast authentication scheme for minimizing of signaling cost between the authentication server and external networks. And we calculate the rate of authentication occurrence in LTE networks using mathematical modeling as well as the change of signaling cost for authentication in various network environments. Finally, we calculate the optimized number of authentication data and show the effectiveness for authentication signaling costs.

• The KIPS Transactions:PartC
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• v.10C no.6
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• pp.727-738
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• 2003

Much research efforts are being exerted for the study of intrusion detection system(IDS). However little work has been for the communication medels and performance eveluation of the IDS. Here we present a communication framework for doing hybrid intrusion detection in which agents are used for local intrusion detections with a centralized data anaysis componenta for a global intrusion detection at multiple domains environment. We also assume the combination of host-based and network-based intrusion detection systems in the oberall framework. From the local domain, a set of information such as alert, and / or log data are reported to the upper level. At the root of the hierarchy, there is a global manager where data coalescing is performed. The global manager delivers a security policy to its lower levels as the result of aggregation and correlation of intrusion detection alerts. In this paper, we model the communication mechanisms for the hybrid IDS and develop a simular using OPNET modeller for the performance evaluation of transmission capabillities for the delivery of data and policy. We present and compare simulation results based on several scenarios focuding on communication delay.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.7-14
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• 2021

The emergence of the automated smart grid has become an essential device for responding to these problems and is bringing progress toward a smart grid-based society. Smart grid is a new paradigm that enables two-way communication between electricity suppliers and consumers. Smart grids have emerged due to engineers' initiatives to make the power grid more stable, reliable, efficient and safe. Smart grids create opportunities for electricity consumers to play a greater role in electricity use and motivate them to use electricity wisely and efficiently. Therefore, this study focuses on power demand management through machine learning. In relation to demand forecasting using machine learning, various machine learning models are currently introduced and applied, and a systematic approach is required. In particular, the GP learning model has advantages over other learning models in terms of general consumption prediction and data visualization, but is strongly influenced by data independence when it comes to prediction of smart meter data.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.583-590
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• 2022

With the release of the Bitcoin source in 2009, cryptocurrencies are continuously developing and expanding the market. Recently, new applicability is expanding centered on NFT coin and metaverse payment service. In particular, the Central Cryptocurrency Exchange actively supports relay transactions between cryptocurrencies or between traditional fiat currencies and cryptocurrencies. The cryptocurrency trading market based on such a central exchange encouraged speculative factors of cryptocurrencies, strongly arousing speculation and futility of cryptocurrencies. In addition, the central cryptocurrency exchange induces the centralization of users and virtual assets, thereby hindering the decentralization and security enhancement strategies of the block chain. Therefore, this study describes the current status and problems of centrally controlled centralized cryptocurrency exchanges in service, and presents a distributed cryptocurrency exchange modeling strategy and major issues as a decentralization model of the exchange. This research can strengthen the anonymity, decentralization, and autonomy of cryptocurrency based on blockchain.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.278-281
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• 2023

연구목적: 본 연구는 요양병원 등 재난취약시설에 재난이 발생할 경우 잔류한 요구조자를 정확하게 파악하여 소방 등 대응기관에 제공하는 APC(Auto People Counting)의 인식률 개선에 목적이 있다. 현재 재난 발생 시 건물 내 요구조자의 현황 파악을 위해 대응기관이 재난 현장에 도착하여 건물관계자에게 직접 물어보고 있다. 이는 요구조자에 대한 부정확한 정보일 가능성이 있어 대응기관의 업무범위가 확대되고 이로인해 구조자의 안전에도 위험이 될 수 있다. APC는 건물내 출입하는 인원을 자동으로 집계하여 실시간 잔류인원 정보를 제공함으로써 재난 시 요구조자 현황을 정확히 파악할 수 있다. 본 연구에서는 APC가 보다 정확하게 출입 인원을 집계할 수 있도록 최적의 인공지능 알고리즘을 선정하는데 목적이 있다. 연구방법: 본 연구에서는 실제 재난취약시설에 설치되어 운영 중인 APC를 대상으로 카메라를 통해 출입 인원의 이미지를 인식하는 알고리즘을 개선하기 위해 CNN모델을 활용하여 베이스라인 모델링을 하였다. 다양한 알고리즘의 성능을 분석하여 상위 7개의 후보군을 선정하고 전이학습 모델을 활용하여 성능이 가장 우수한 최적의 알고리즘을 선정하는 방법으로 연구를 수행하였다. 연구결과: 실험결과 시간과 성능이 가장 좋은 Densenet201, Resnet152v2 모델의 정밀도와 재현율을 확인한 결과 모든 라벨에 대해서 정확도 100%를 나타내는 것을 확인할 수 있었다. 이 중 Densenet201 모델이 더 높은 성능을 보여주었다. 결론: 다양한 인공지능 알고리즘 중 APC에 적용할 수 있는 최적의 알고리즘을 선정하였고 이는 APC의 인식률을 개선하여 재난시 요구조자의 정보를 정확하게 파악하여 신속하고 안전한 구조작업이 가능할 것이다. 이는 요구조자의 안전한 구조뿐만 아니라 구조작업을 수행하는 구조자의 안전을 확보하는 데 기여할 것으로 기대된다. 향후 연무 등 다양한 재난상황에서 재난취약시설 내 출입인원을 정확하게 파악할 수 있도록 알고리즘 분석 및 학습에 대한 추가 연구가 요구된다.

• Journal of Industrial Convergence
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• v.22 no.5
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• pp.39-48
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• 2024

Due to COVID-19, much research has been conducted on learning loss and educational gaps due to the postponement of the start of school and prolonged online distance learning, and most of the research has focused on the phenomenon of educational gaps. If a pandemic situation like this occurs in the future, fundamental policies are needed to resolve the educational gap. A fundamental solution requires not only an understanding of the educational gap phenomenon, but also the structure behind the phenomenon. Therefore, from a structuralist perspective, this study sought to model the educational gap caused by COVID-19 as a prototype of systems thinking and identify its structure. In addition, we looked at the unintended consequences resulting from policies aimed at resolving existing educational gaps. In order to respond to similar disaster situations in the future, policies for resolving the digital gap, support for basic academic skills, quality improvement for distance learning, and self-directed learning were discussed based on the structure of this study.

• Journal of KIISE:Information Networking
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• v.32 no.3
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• pp.279-290
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• 2005

Recently, as the serious damage caused by DDoS attacks increases, the rapid detection and the proper response mechanisms are urgent. However, existing security mechanisms do not effectively defend against these attacks, or the defense capability of some mechanisms is only limited to specific DDoS attacks. In this paper, we propose a detection architecture against DDoS attack using data mining technology that can classify the latest types of DDoS attack, and can detect the modification of existing attacks as well as the novel attacks. This architecture consists of a Misuse Detection Module modeling to classify the existing attacks, and an Anomaly Detection Module modeling to detect the novel attacks. And it utilizes the off-line generated models in order to detect the DDoS attack using the real-time traffic. We gathered the NetFlow data generated at an access router of our network in order to model the real network traffic and test it. The NetFlow provides the useful flow-based statistical information without tremendous preprocessing. Also, we mounted the well-known DDoS attack tools to gather the attack traffic. And then, our experimental results show that our approach can provide the outstanding performance against existing attacks, and provide the possibility of detection against the novel attack.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.3
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• pp.445-457
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• 2013

This paper is about the study to build a quantitative methodology to assess cyber threats and vulnerabilities on control systems. The SCADA system in power industry is one of the most representative and biggest control systems. The SCADA system was originally a local system but it has been extended to wide area as both ICT and power system technologies evolve. Smart Grid is a concept to integrate energy and IT systems, and therefore the existing cyber threats might be infectious to the power system in the integration process. Power system is operated on a real time basis and this could make the power system more vulnerable to the cyber threats. It is a unique characteristic of power systems different from ICT systems. For example, availability is the most critical factor while confidentiality is the one from the CIA triad of IT security. In this context, it is needed to reflect the different characteristics to assess cyber security risks in power systems. Generally, the risk(R) is defined as the multiplication of threat(T), vulnerability(V), and asset(A). This formula is also used for the quantification of the risk, and a conceptual methodology is proposed for the objective in this study.

• Journal of the Korean Geophysical Society
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• v.9 no.1
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• pp.47-62
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• 2006

More than 70% of Korean Peninsula is consisted of mountains, so that lots of roads, rail-roads and tunnel,which play a pivotal role in the industry activity, are existed along the rock-slope and in the rock-mass. Thus,it is urgent that tegration of management system through the optimum survey and design of rock-slope excavation, proper stabilization method and database of rock-slope. However, conventional methods have shortcoming with the economy of survey time and human resources, and the overcome of difficulties of approach to the in-situ rock-slope. To overcome the limitation of conventional method, this paper proposed the development of remote measurement system using Terrestrial Laser Scanning System. The method using Terrestrial 3D Laser Scanning System, which can get 3D spatial information on the rock-slope and2)Dept. Geosystem Engineering, Kangwon National University, Korea tunnel, has an advantage of reduction of measurement time and the overcome of difficulties of approach to the in-situ rock-slope/dam/tunnel. In the case of rock-slope, through the analysis of 3D modeling of point-cloud by Terrestrial Laser Scanning System, orientation of discontinuity, roughness of joint surface, failure shape and volume were successively achieved. in the case of tunnel face, through reverse-engineering, monitoring of displacement was possible.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.641-650
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• 2010

Color image sensors (CIS) output color images through image sensors and image signal processing. Image sensors that convert light to electrical signal are divided into CMOS image sensor and CCD image sensor according to transferring method of signal charge. In general, a CIS has RGB output signals from tri-stimulus XYZ of the scene through image signal processing. This paper presents an adaptive colorimetric analysis method to obtain chromaticity and luminance using CIS under various environments. An image sensor for the use of colorimeter is characterized based on the CIE standard colorimetric observer. We use the method of least squares to derive a colorimetric characterization matrix between camera RGB output signals and CIE XYZ tristimulus values. We first survey the camera characterization in the standard environment then derive a SGL(shutter-gain-level) function which is relationship between luminance and auto exposure (AE) characteristic of CIS, and read the status of an AWB(auto white balance) function. Then we can apply CIS to measure luminance and chromaticity from camera outputs and AE resister values without any preprocessing. Camera RGB outputs, register values, and camera photoelectric characteristic are used to analyze the colorimetric results for real scenes such as chromaticity and luminance. Experimental results show that the proposed method is valid in the measuring performance. The proposed method can apply to various fields like surveillant systems of the display or security systems.