• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.6A
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• pp.600-607
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• 2007

In this paper, we propose a MLKA (Multi-Level Keep-Alive) algorithm based on PRCG (Periodic In this paper, we propose a MLKA (Multi-Level Keep-Alive) algorithm based on PRCG (Periodic Ranging Code Group), in which periodic ranging codes are divided into groups. The AP (Access Point) performs this algorithm when a periodic ranging code arrives at the AP in a WiBro (Wireless Broadband Internet) system. In order to increase the traffic radio bandwidth resource efficiency in this system, we propose the multi-level keep-alive algorithm for finding abnormal AT (Access Terminal). From simulation results, it is verified our proposed MLKA algorithm based on PRCG can provide higher traffic radio resource efficiency compared to message-driven keep-alive algorithms.

• Journal of KIISE:Information Networking
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• v.36 no.2
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• pp.69-79
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• 2009

Today's Internet is one of the necessaries of our life. Anomalies of the Internet provoke social problems. For that reason, Internet Measurement which studies characteristics on Internet traffic attracts pubic attention. Recently, Traffic Dispersion Graph (TDG), a novel traffic analysis method, was proposed. The TDG is not a statistical analysis method but a graphical visualization method on interactions among network components. In this paper, we propose a new anomaly detection paradigm and its technique using TDG. The existing studies have focused on detecting anomalous packets of flows. On the other hand, we focus on detecting the sources of anomalous traffic. To realize our paradigm, we designed the TDG Clustering method. Through this method, we could classify anomalous hosts infected by various worm viruses. We obtained normal traffic through dropping traffic of the anomalous hosts. Especially, we expect that the TDG clustering method can be applied to real-time anomaly detection because calculations of the method are fast.

• Smart Structures and Systems
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• v.9 no.3
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• pp.287-301
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• 2012

It is well known that overloaded vehicles may cause severe damages to bridges, and how to estimate and evaluate the status of the overloaded vehicles passing through bridges become a challenging problem. Therefore, based on the monitored strain data from a structural health monitoring system (SHM) installed on a bridge, a method is recommended to identify and analyze the probability of overloaded vehicles. Overloaded vehicle loads can cause abnormity in the monitored strains, though the abnormal strains may be small in a concrete continuous rigid frame bridge. Firstly, the abnormal strains are identified from the abundant strains in time sequence by taking the advantage of wavelet transform in abnormal signal identification; secondly, the abnormal strains induced by heavy vehicles are picked up by the comparison between the identified abnormal strains and the strain threshold gotten by finite element analysis of the normal heavy vehicle; finally, according to the determined abnormal strains induced by overloaded vehicles, the statistics of the overloaded vehicles passing through the bridge are summarized and the whole probability of the overloaded vehicles is analyzed. The research shows the feasibility of using the monitored strains from a long-term SHM to identify the information of overloaded vehicles passing through a bridge, which can help the traffic department to master the heavy truck information and do the damage analysis of bridges further.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.5
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• pp.1169-1177
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• 2018

Modern society is a period of rapid digital transformation. This digital-centric business proliferation offers convenience and efficiency to businesses and individuals, but cyber threats are increasing. In particular, cyber attacks are becoming more and more intelligent and precise, and various attempts have been made to prevent these attacks from being discovered. Therefore, it is increasingly difficult to respond to such attacks. According to the cyber kill chain concept, the attacker penetrates to achieve the goal in several stages. We aim to detect one of these stages and neutralize the attack. In this paper, we propose a method to detect anomalous traffic caused by an agent attacking an external attacker, assuming that an agent executing a malicious action has been introduced in advance due to various reasons such as a system error or a user's mistake.

• The KIPS Transactions:PartC
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• v.12C no.6 s.102
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• pp.855-864
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• 2005

In this paper, we propose an intrusion detection system(IDS) architecture which can detect and respond against the generation of abnormal traffic such as malicious code and Internet worms. We model the system, design and implement a simulator using OPNET Modeller, for the performance analysis on the response capacity of alert information in the proposed system. At first, we model the arrival process of alert information resulted from abnormal traffic. In order to model the situation in which alert information is intensively produced, we apply the IBP(Interrupted Bernoulli Process) which may represent well the burstiness of traffic. Then we perform the simulation in order to gain some quantitative understanding of the system for our performance parameters. Based on the results of the performance analysis, we analyze factors which may hinder in accelerating the speed of security node, and would like to present some methods to enhance performance.

• The KIPS Transactions:PartC
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• v.12C no.5 s.101
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• pp.649-658
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• 2005

Since the Network based attack Is extensive in the real state of damage, It is very important to detect intrusion quickly at the beginning. But the intrusion detection using supervised learning needs either the preprocessing enormous data or the manager's analysis. Also it has two difficulties to detect abnormal traffic that the manager's analysis might be incorrect and would miss the real time detection. In this paper, we propose a traffic attributes correlation analysis mechanism based on self-organizing maps(SOM) for the real-time intrusion detection. The proposed mechanism has three steps. First, with unsupervised learning build a map cluster composed of similar traffic. Second, label each map cluster to divide the map into normal traffic and abnormal traffic. In this step there is a rule which is created through the correlation analysis with SOM. At last, the mechanism would the process real-time detecting and updating gradually. During a lot of experiments the proposed mechanism has good performance in real-time intrusion to combine of unsupervised learning and supervised learning than that of supervised learning.

• Korean Journal of Culture and Social Issue
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• v.16 no.3
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• pp.267-287
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• 2010

This study aimed to improve the Traffic Accident Management System's validity and reliability, so the system could help classify and judge the human factors that correlate with traffic accidents. We took traffic accident research and analysis systems of United States and United Kingdom and certain related, former studies into account in building our test system. Next, we used the test system's criteria to re-analyze 502 Gyeonggi province accident records from 2008. We compared the results to existing systems' results to verify the test system's validity and reliability. These results indicated the necessity of removing some uncertain items from the existing systems and adding in some new items from the test system. This should help improve understanding of what happens at traffic accident scenes and of the sources of drivers' abnormal, reckless behavior. We introduce suggestions for improving the Traffic Accident Management System and research concepts for further studies.

• Journal of Korean Society of Transportation
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• v.32 no.5
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• pp.497-502
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• 2014

As ground air traffic control at the airport is one of the most important tasks in air transport, attention to the development of a related simulator has expanded all around the world. For this reason, this research describes the characteristics and advantages of this advanced aerodrome traffic control simulator, developed in South Korea, as well as its linkage with A-SMGCS, which is planned to be developed in the future. One of the characteristics of this simulator is that it is possible to train an air traffic controller independently, especially under various conditions such as in different weathers and normal or abnormal circumstances. Therefore, this aerodrome traffic control simulator, through the comprehensive training under various conditions, will contribute to aviation safety and airport capacity enhancement training.

• Journal of Auto-vehicle Safety Association
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• v.10 no.3
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• pp.32-37
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• 2018

Recently, the driver can be assisted by the advanced active safety devices such as ADAS from road traffic risks. With this system, driver and passenger may freed from can driving tasks or kept eyes on forward direction while on the road. Help from adoptive cruise control, auto parking and newly develped automated driving vehicles technologies, the driver positions will vary significantly from the current standard driver position during the travel time. On this hypothesis, the objective of this study is analyze the behavior and injuries of drivers in the event of frontal impact under these abnormal driver position. Based on the KNCAP frontal impact testing method, this simulation matrix was set-up with dummies of 5 th tile female Hybrid III dummy and 50 th tile male Hybrid III dummy. The small sedan type passenger car was modeled in this simulation. The series of simulation was performed to compare the injuries and behaviour of each dummy, varying the seating status and seat position of each dummy.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.11
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• pp.2281-2285
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• 2009

Powerline communication is the data signal which is modulated by carrier frequency through the installed powerline at in-home or office is transmitted and received signals are separated into data signal with using band-pass filter which cent-frequency is carrier frequency. The home gateway, an equipment which works as an gateway for ubiquitous home network, relays all functions of a home network. The home gateway must always be connected in order to provide seamless services. However it gives unfavorable power consumption. Therefore the needs for working in maximum power saving mode while there is no data traffic and for invoking to the normal function when it is necessary. So, in this paper we survey the development of low power PLC modem monitoring of power consumption and breaking abnormal power in the home Network.