• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.6
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• pp.1185-1195
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• 2014

Domestic and international CERTs are carrying out security monitoring and response services based on security devices for intrusion incident prevention and damage minimization of the organizations. However, the security monitoring and response service has a fatal limitation in that it is unable to detect unknown attacks that are not matched to the predefined signatures. In recent, many approaches have adopted the darknet technique in order to overcome the limitation. Since the darknet means a set of unused IP addresses, no real systems connected to the darknet. Thus, all the incoming traffic to the darknet can be regarded as attack activities. In this paper, we present a collection and analysis method of malicious URLs based on darkent traffic for advanced security monitoring and response service. The proposed method prepared 8,192 darknet space and extracted all of URLs from the darknet traffic, and carried out in-depth analysis for the extracted URLs. The analysis results can contribute to the emergence response of large-scale cyber threats and it is able to improve the performance of the security monitoring and response if we apply the malicious URLs into the security devices, DNS sinkhole service, etc.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.577-586
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• 2018

In this study, traffic safety technology was developed for rural areas by reviewingthe relevant literature and data from the Traffic Accident Analysis System for the Chungcheong region.The goal is to reduce traffic accidents in small regional cities and rural areas in Korea. A road shoulder recognition light was developed to fit the pedestrian characteristics of the people using transportation in rural areas. It also minimizes damage to crops due to light pollution from traffic lights and street lights, and it supplements problems of damage from collision with vehicles and agricultural machines. The efficiency of the technology developed in this study was verified by comparing and analyzing the number of traffic accidents and the saved cost before and after its installation. A test bedwas established based on rural areas and is being evaluated for its applicability and effectiveness. It is expected that the reliability of such facilities could be improved through continuous studies, data collection, and analysis.

• Journal of Korean Society of Transportation
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• v.35 no.3
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• pp.220-233
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• 2017

Traffic volumes are fundamental data widely used in various traffic analysis, such as origin-and-destination establishment, total traveled kilometer distance calculation, congestion evaluation, and so on. The low number of links collecting the traffic-volume data in a large urban highway network has weakened the quality of the analyses in practice. This study proposes a method to estimate the traffic volume data on a highway link where no collection device is available by introducing a spatial statistic technique with (1) the traffic-volume data from TOPIS, and National Transport Information Center in the Ministry of Land, Infrastructure, and (2) the navigation data from private navigation. Two different component models were prepared for the interrupted and the uninterrupted flows respectively, due to their different traffic-flow characteristics: the piecewise constant function and the regression kriging. The comparison of the traffic volumes estimated by the proposed method against the ones counted in the field showed that the level of error includes 6.26% in MAPE and 5,410 in RMSE, and thus the prediction error is 20.3% in MAPE.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.119-131
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• 2024

Understanding accurate traffic performance is crucial for ensuring efficient highway operation and providing a sustainable mobility environment. On the other hand, an immediate and precise estimation of highway traffic performance faces challenges because of infrastructure and technological constraints, data processing complexities, and limitations in using integrated big data. This paper introduces a framework for estimating traffic performance by analyzing real-time data sourced from toll collection systems and dedicated short-range communications used on highways. In particular, this study addresses the data errors arising from segmented information in data, influencing the individual travel trajectories of vehicles and establishing a more reliable Origin-Destination (OD) framework. The study revealed the necessity of trip linkage for accurate estimations when consecutive segments of individual vehicle travel within the OD occur within a 20-minute window. By linking these trip ODs, the daily average highway traffic performance for South Korea was estimated to be248,624 thousand vehicle kilometers per day. This value shows an increase of approximately 458 thousand vehicle kilometers per day compared to the 248,166 thousand vehicle kilometers per day reported in the highway operations manual. This outcome highlights the potential for supplementing previously omitted traffic performance data through the methodology proposed in this study.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1266-1276
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• 2003

Multimedia information containing voice and image is transmitted on Internet, which is ten times or hundred times larger than ordinary information. Analysis types for network management in this environment consist of a real time analysis, a basic analysis and an intensive analysis. The intensive analysis is useful for gathering the trend information of specific objects periodically for certain period in order to monitor network status. When SNMP is applied to collect the trend information of intensive analysis, it brings on the increase of network load, the delay of response time and the decrease of data collection accuracy since an agent responds to manager's every polling. In this paper, an efficient SNMP is proposed and implemented to add time variables in the existing SNMP PDU. It minimizes unnecessary traffic in the intensive analysis between manager and agent, and collects trend information more accurately. The results of experiments show that it has compatibility with the existing SNMP, decreases the amount of network traffic greatly and increases the accuracy of data collection.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.4
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• pp.107-117
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• 2008

OBE(On Board Equipment) of IR(Infrared)/RF(Radio Frequence)-DSRC(Dedicated Short Range Communication) are set up 1.25 million cars because Korea Highway Cooperation supplied in HiPass(Domestic Electronic Toll Collection System). But this DSRC system has strength and weakness of service for BIS(Bus Information System) or UTIS(Urban Traffic Information System) because BIS and UTIS are required vary high communication's performance and management. In this paper, Efficiency of IR/RF-DSRC is analyzed performance of MAC(Medium Access Control) by computer simulation for services of BIS or UTIS, so Suggested to be commensurated with medium of there service. Specially, DSRC is needed high mobility and throughput in the vary short communication range, so Analysed the transmission rate of data in each communication medium over the specific character of the MAC frame.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.116-126
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• 2013

Weather factor to affect driver's driving environment are due to changes in weather conditions is caused rainfall, snowfall, fog etc and the reducing of road capacity and because deteriorating weather could be affect the headway and vehicle speed and the decrease in lane caused by an accident occurs that was analyzed that bad weather occur congestion greater than on the clear day. Bad weather to reduce of the driver's visibility was analysed the sensitive to changes in travel speed and traffic accident to appears high characteristics according to weather conditions on the expressway(higher speed) than general road. As a result, visibility have been determined to be important factor in changes of the highway traffic flow characteristics. Therefore, in this study, we selected traffic volume and travle speed that have a major impact on high-speed expressway basic segments as importance effect factor and we selected to subject of analysis among the Metropolitan Expressway that it could be obtained certain level of traffic volume data and we studied the changing of expressway traffic flow due to change visibility after the collecting of meteorological and traffic data. In order to perform this study, data collection and analysis methods were established through the existing literature and we had selected level of visibility of the expressway and we had performed the statistical verification. Finally, we had calculated the rate of change of expressway traffic flow characteristics due to visibility and we had come up with a way to apply at capacity and service level analysis.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.4
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• pp.14-27
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• 2009

Collection of invaluable real-time traffic data becomes available under ubiquitous transportation sensor networks (UTSN). Various research efforts have been made to utilize such useful data for deriving more accurate and reliable traffic information. This study presented a novel concept of decentralized traffic information and method to process traffic data which are obtained from inter-vehicle communications under the UTSN. In addition, an experimental evaluation to investigate the feasibility of the proposed method using probe vehicle data. Predictive travel times were estimated and evaluated for the feasibility investigation. Technical issues were derived and discussed to fully implement the proposed system. The outcomes of this study would be used as a guideline in designing better next-generation traffic information systems.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.67-74
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• 2022

In recent, the number of real-time traffic information sources and providers has increased as increasing smartphone users and intelligent transportation system facilities installed at roadways including vehicle detection system (VDS), dedicated short-ranged communications (DSRC), and global positioning system (GPS) probe vehicle. The accuracy of such traffic information would vary with these heterogeneous information sources or spatiotemporal traffic conditions. Therefore, the purpose of this study is to propose an empirical strategy of heterogeneous information fusion to improve the accuracy of real-time traffic information. To carry out this purpose, travel speed data collection based on the floating car technique was conducted on 227 freeway links (or 892.2 km long) and 2,074 national highway links (or 937.0 km long). The average travel speed for 5 probe vehicles on a specific time period and a link was used as a ground truth measure to evaluate the accuracy of real-time heterogeneous traffic information for that time period and that link. From the statistical tests, it was found that the proposed fusion strategy improves the accuracy of real-time traffic information.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.6
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• pp.187-194
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• 2020

This paper proposes a website fingerprinting method using ensemble learning over a Tor network that guarantees client anonymity and personal information. We construct a training problem for website fingerprinting from the traffic packets collected in the Tor network, and compare the performance of the website fingerprinting system using tree-based ensemble models. A training feature vector is prepared from the general information, burst, cell sequence length, and cell order that are extracted from the traffic sequence, and the features of each website are represented with a fixed length. For experimental evaluation, we define four learning problems (Wang14, BW, CW_T, CW_H) according to the use of website fingerprinting, and compare the performance with the support vector machine model using CUMUL feature vectors. In the experimental evaluation, the proposed statistical-based training feature representation is superior to the CUMUL feature representation except for the BW case.