• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1670-1675
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• 2020

In this study, to provide the basis for establishing effective network based countermeasures against DRDoS(Distributed Reflection Denial of Service) attacks, we propose a new 'DRDoS attack multi-level detection method' that identifies the network based characteristics of DRDoS and applies probability and statistical techniques. The proposed method removes the limit to which normal traffic can be indiscriminately blocked by unlimited competition in network bandwidth by amplification of reflectors, which is characteristic of DRDoS. This means that by comparing 'Server to Server' and 'Outbound Session Incremental' for it, accurate DRDoS identification and detection is possible and only statistical and probabilistic thresholds are applied to traffic. Thus, network-based information security systems can take advantage of this to completely eliminate DRDoS attack frames. Therefore, it is expected that this study will contribute greatly to identifying and responding to DRDoS attacks.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.2
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• pp.54-59
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• 2010

The flight deck crew must manage complexity during daily flight operations. The Airline may obtain data regarding threats and errors through LOSA(Line Operations Safety Audits) on normal flights as predictive safety tool in Safety Management System of the Airline to actively improve the systems such as SOP(Standard Operation Procedure), training, evaluation and the TEM(Threat and Error Management) for the flight deck crew. The flight deck crew make errors when they fail managing threats. The crew mismanage around ten percent of threats and commit errors. The major mismanaged threats are aircraft malfunction, ATC(Air Traffic Communication), and wether threats. The effective countermeasures of TEM for manageing threats are leadership, workload management, monitor & cross check, Vigilance, communication environment and cooperation of the crew. It is important that organizations must monitor for the hazards of threats and improve system for the safer TEM environments.

• Journal of Korean Society of Transportation
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• v.28 no.5
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• pp.17-29
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• 2010

The main objective of this study is to consider the necessity of introducing owner expenses in estimating the cost of traffic accidents, as is done in some advanced countries. It is known as "owner cost" in the U.S, "enterprise project price" in Japan, and "human cost" in the U.K. To achieve this, the seriousness and present state of post-traumatic stress disorder (PTSD) of traffic accident offenders, which is generally not observed when traffic accidents occur, are evaluated; countermeasures reflecting personal characteristics are prepared according to degree of affliction. The results could be summarized as follows. First, the present condition and seriousness of PTSD from traffic accidents that has been estimated only within the accidents offenders are evaluated through a survey. Second, a distinction analysis model is developed. 'Insomnia caused by accidents' and 'mental daunting in accident situations or similar ones during driving' are chosen as the variables of the discriminant. Third, as a result of the construction of an Ordered Probit Model to comprehend the seriousness of PTSD, the variables turns out in the order of 'seriousness of the most damaged victim, 'nightmare about the accident', 'insomnia experience', 'mental daunting during driving', 'gender', and 'major driving area'. Finally, the cures reflecting characteristics of gender and region are suggested, which are preferred for degree of seriousness of PTSD. The analysis shows that the method to minimize the damage, such as decline of work efficiency, by moving ahead the rehabilitation of the offenders would be suggested and this could minimize the direct and indirect damages that could happen to business owners for whom the drivers work.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.55-65
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• 2021

In January 2020, the first COVID-19 confirmed patient occurred in Korea, and the pandemic continues to this day. In unprecedented situations, COVID-19 also affected the transportation sector, and there were no appropriate measures against changes in traffic volume and use of public transportation due to changes in citizens' lifestyles. Currently, each local government has not established separate measures for pandemic disease measures. In order to establish future disease countermeasures in the transportation sector, a predictive model was developed by analyzing the traffic volume and the number of public transportation uses, and conducting correlation analysis with the current status of COVID-19. As a result of the analysis, the traffic volume decreased, but the traffic volume decreased due to the increase in personal transportation, but it did not reach the number of public transportation uses. In addition, it was analyzed that the use of public transportation was initially affected by the number of confirmed cases, but over time, it was more sensitive to death and mortality than to the number of confirmed cases.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.3
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• pp.679-690
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• 2015

The need to remove the cause of traffic accidents by improving the engineering system for a vehicle and the road in order to minimize the accident hazard. This is likely to cause traffic accident continue to take a large and significant social cost and time to improve the reliability and efficiency of this generally poor road, thereby generating a lot of damage to the national traffic accident caused by improper environmental factors. In order to minimize damage from traffic accidents, the cause of accidents must be eliminated through technological improvements of vehicles and road systems. Generally, it is highly probable that traffic accident occurs more often on roads that lack safety measures, and can only be improved with tremendous time and costs. In particular, traffic accidents at intersections are on the rise due to inappropriate environmental factors, and are causing great losses for the nation as a whole. This study aims to present safety countermeasures against the cause of accidents by developing an intersection Traffic safety evaluation model. It will also diagnose vulnerable traffic points through BPA (Back -propagation algorithm) among artificial neural networks recently investigated in the area of artificial intelligence. Furthermore, it aims to pursue a more efficient traffic safety improvement project in terms of operating signalized intersections and establishing traffic safety policies. As a result of conducting this study, the mean square error approximate between the predicted values and actual measured values of traffic accidents derived from the BPA is estimated to be 3.89. It appeared that the BPA appeared to have excellent traffic safety evaluating abilities compared to the multiple regression model. In other words, The BPA can be effectively utilized in diagnosing and practical establishing transportation policy in the safety of actual signalized intersections.

• Journal of Korea Port Economic Association
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• v.28 no.4
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• pp.99-120
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• 2012

The ongoing development of Distriparks, the increase in workers inside the warehouses, and the growth in traffic volume have shifted the attention of the many D.C. operators on how to utilize their warehouse spaces more profitably and economically. A total of 550 cars and trucks are illegally parked at the distribution centers everyday. To meet these challenges, port authorities are looking closely at how they can establish effective countermeasures to solve this problem and satisfy customers of the Distripark. In order to answer these questions, this article sought to identity and analyze the current status of the illegal parking issues and main causes of that phenomena. In addition to summarizing an actual outcomes of the illegal parking problems, the research also examines the legal and practical countermeasures of this issues. Finally this research tries to find future solutions for ports in the Distripark development process, with particular reference to the legal and managerial aspects.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.1994-2005
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• 2015

Voice over IP (VoIP) is a technology for the delivery of voice communications and multimedia sessions over Internet Protocol (IP) networks. Instead of being transmitted over a circuit-switched network, however, the digital information is packetized, and transmission occurs in the form of IP packets over a packet-switched network which consist of several layers of computers. VoIP Service that used the various techniques has many advantages such as a voice Service, multimedia and additional service with cheap cost and so on. But the various frauds arises using VoIP because VoIP has the existing vulnerabilities at the Internet and based on complex technologies, which in turn, involve different components, protocols, and interfaces. According to research results, during in 2012, 46 % of fraud calls being made in VoIP. The revenue loss is considerable by fraud call. Among we will analyze for Toll Bypass Fraud by the SIM Box that occurs mainly on the international call, and propose the measures that can detect. Typically, proposed solutions to detect Toll Bypass fraud used DPI(Deep Packet Inspection) based on a variety of detection methods that using the Signature or statistical information, but Fraudster has used a number of countermeasures to avoid it as well. Particularly a Fraudster used countermeasure that encrypt VoIP Call Setup/Termination of SIP Signal or voice and both. This paper proposes the solution that is identifying equipment of Toll Bypass fraud using those countermeasures. Through feature of Voice traffic analysis, to detect involved equipment, and those behavior analysis to identifying SIM Box or Service Sever of VoIP Service Providers.

• Journal of Korean Society of Transportation
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• v.30 no.4
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• pp.95-106
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• 2012

Driver's capability of identifying the change in freeway alignments and environments is one of important factors associated with traffic safety on freeways. In particular, driver's visibility and recognition capability are highly dependent on the altitude of the sun by sunset, sunrise, and nighttime. The purpose of this study is to identify the characteristics of geometric conditions affecting crash occurrences at sunset, sunrise, and nighttime. Poisson and negative binomial regressions were adopted to predict freeway crash frequency in this study. Freeway crash data during 2007~2010 were used for developing the crash frequency models. A set of variables representing the characteristics of geometric conditions were identified as significant ones affecting crash occurrences. The results of this study would be useful in deriving effective countermeasures for preventing traffic crashes that mainly occur at sunset, sunrise, and nighttime on freeways.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.157-172
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• 2024

Autonomous driving technology, when commercialized, has the potential to improve the safety, mobility, and environmental performance of transportation networks. However, safe autonomous driving may be hindered by poor sensor performance and limitations in long-distance detection. Therefore, cooperative autonomous driving that can supplement information collected from surrounding vehicles and infrastructure is essential. In addition, since HDVs, AVs, and CAVs have different ranges of perceivable information and different response protocols, countermeasures are needed for mixed traffic that occur during the transition period of autonomous driving technology. There is a lack of research on traffic flow optimization that considers the penetration rate of autonomous vehicles and the different characteristics of each road segment. The objective of this study is to develop weights based on safety, operational, and environmental factors for each infrastructure control use case and autonomous vehicle MPR. To develop an integrated evaluation index, infra-guidance AHP and hybrid AHP weights were combined. Based on the results of this study, it can be used to give right of way to each vehicle to optimize mixed traffic.

• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.43-51
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• 2011

Since a variety of factors are associated with crash occurrence, the analysis of causes of crash is a hard task for traffic researchers and engineers. Among contributing factors leading to crash, the characteristics of driver is of keen interest. This study attempted to identify factors affecting the severity of pedestrian in the collision between pedestrian and vehicle. In particular, our analyses were focused on the novice driver. A binary logistic regression technique was adopted for the analyses. The results showed that driver's age, crash location, and the frequency of violations were dominant factors for the severity. Findings are expected to be useful information for deffective policy- and education-based countermeasures.