• Journal of The Geomorphological Association of Korea
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• v.27 no.2
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• pp.65-80
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• 2020

This paper deals with risk assessment of life in a landslide-prone area by a GIS-based modeling method. Landslide susceptibility maps can provide a probability of landslide prone areas to mitigate or proper control this problems and to take any development plan and disaster management. A landslide inventory map of the study area was prepared based on past historical information and aerial photography analysis. A total of 550 landslides have been counted at the whole study area. The extracted landslides were randomly selected and divided into two different groups, 50% of the landslides were used for model calibration and the other were used for validation purpose. Eleven causative factors (continuous and thematic) such as slope, aspect, curvature, topographic wetness index, elevation, forest type, forest crown density, geology, land-use, soil drainage, and soil texture were used in hazard analysis. The correlation between landslides and these factors, pixels were divided into several classes and frequency ratio was also extracted. Eventually, a landslide susceptibility map was constructed using a logistic regression model based on entire events. Moreover, the landslide susceptibility map was plotted with a receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC) and tried to extract a success rate curve. Based on the results, logistic regression produced an 85.18% accuracy, so we believed that the model was reliable and acceptable for the landslide susceptibility analysis on the study area. In addition, for risk assessment, vulnerability scale were added for social thematic data layer. The study area predictive landslide affected pixels 2,000 and 5,000 were also calculated for making a probability table. In final calculation, the 2,000 predictive landslide affected pixels were assumed to run. The total population causalities were estimated as 7.75 person that was relatively close to the actual number published in Korean Annual Disaster Report, 2006.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3B
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• pp.243-252
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• 2011

The change of rainfall pattern due to recent climate change increases the occurrence probability of drought in Korea. Unlike other natural disasters, a drought has long duration, extensive area subject to damage, and greater socioeconomic damage than other disasters. In order to evaluate drought severity, meteorological drought indices are mainly used in practice. This study presents a more realistic method to evaluate drought severity considering drought climate factors as well as socioeconomic factors which are vulnerable to disaster. To perform a spatial evaluation of drought risk in Gyeongsang-do, drought risk was defined and analyzed through the hazard index and the vulnerability index. The drought hazard index was spatially assessed using the drought index and GIS. The drought vulnerability index was also spatially assessed using the 5 socioeconomic factors. As a result, the drought risks were compared and used for evaluating regional drought risk considering regional characteristics of Gyeongsang-do.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.2
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• pp.1-23
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• 2018

This study aims to propose a way for evaluating thermal environment vulnerability associated with policy to improve thermal environment. For this purpose, a variety of indices concerning thermal vulnerability assessment and adaptation policies for climate change applied to 17 Korean cities were reviewed and examined. Finally, 15 indices associated with policies for improving thermal environment were selected. The selected indices for thermal vulnerability assessment were applied to Daegu Metropolitan City of South Korea as a case study. As results, 15 vulnerability maps based on the standardized indices were established, and a comprehensive map with four grades of thermal vulnerability were established for Daegu Metropolitan City. As results, the area with the highest rated area in the first-grade(most vulnerable to heat) was Dong-gu, followed by Dalseo-gu and Buk-gu, and the highest area ratio of the first-grade regions was Ansim-1-dong in Dong-gu. Based on the standardized indices, the causes of the thermal environment vulnerability of Ansim-1-dong were accounted for the number of basic livelihood security recipients, the number of cardiovascular disease deaths, heat index, and Earth's surface temperature. To improve the thermal environment vulnerability of Ansim-1-dong, active policy implementation is required in expansion and maintenance of heat wave shelters, establishment of database for the population with diseases susceptible to high temperature environments, expansion of shade areas and so on. This study shows the applicability of the vulnerability assessment method linked with the policies and is expected to contribute to the strategic and effective establishment of thermal environment policies in urban master district plans.

• Journal of Korean Society of Rural Planning
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• v.21 no.2
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• pp.11-21
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• 2015

This study carried out evaluation of vulnerability in accessability and functionality using road network that was extracted from Intelligent Transportation System(ITS) and digital map. It was built in order to figure out accessability that locational data which include community center, public facilities, medical facilities and highway IC. The method for grasping functionality are Digital Elevation Model(DEM) and land slide hazard map provided by Korea Forest Service. The evaluation criteria for figure out accessability was set to related comparison of average time in urban area. Functionality value was calculated by the possibility of backing the vehicle possibility of snowfall and landslides. At last, this research computed weighting value through Analytic Hierarchy Process (AHP), calculated a vulnerable score. As the result, the accessability of rural village came out that would spend more time by 1.4 to 3.2 times in comparison with urban area. Even though, vulnerability of the road by a snowfall was estimated that more than 50% satisfies the first class, however, it show up that the road were still vulnerable due snowing because over the 14% of the road being evaluated the fifth class. The functionality has been satisfied most of the road, however, It was vulnerable around Lake Daechung and Piban-ryung, Yumti-jae, Suriti-jae where on the way Boeun. Also, the fifth class road are about 35 km away from the city hall on distance, take an hour to an hour and a half. The fourth class road are about 25 km away from the city hall on distance, take 25 min to an hour. The other class of the road take in 30 min from the city hall or aren't affected of weather and have been analyzed that a density of road is high. In A result that compare between distribution and a housing density came out different the southern and the eastern area, so this result could be suggested quantitative data for possibility of development.

• Journal of Bio-Environment Control
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• v.26 no.2
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• pp.87-99
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• 2017

Recently the increase in an abnormal climate events and meteorological disasters which causes a great damage to greenhouse facilities. To minimize and evaluate the expected damages it is necessary to prepare countermeasures and a management system in advance. For this purpose, a quantitative analysis of weather and abnormal climate are needed to investigate protected cultivation areas which are vulnerable to natural disasters. This study focused on protected cultivation areas in Jeolla province, South Korea. Surrogate variables were calculated to analyze the vulnerable areas to meteorological disasters, and spatial distribution analysis was also performed by using GIS to present vulnerable areas on map. The map thus created and was compared with actual data of damages by meteorological disasters which occurred in target areas. The result of the comparison is as follows: About 50% of the target areas showed an agreement between the map created in this study and the actual data, these areas includes Gwangju metropolitan city, Naju city, Yeongam County, Jangseong County, Hampyeong County, and Haenam County. On the other hand, other areas, including Gunsan city, Mokpo city, and Muan County, suffered low damage in spite of high levels of vulnerability to meteorological disasters. This result was considered to be affected by such variables as different structural designs and management systems of greenhouses by region. This study carried out an analysis of meteorological data to find out more detailed vulnerability to protected cultivation area and to create a map of vulnerable protected cultivation areas. In addition, the map was compared with the record of natural disasters to identify actual vulnerable areas. In conclusion, this study can be utilized as basic data for preventing and reducing damages by meteorological disasters in terms of design and management of greenhouses.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.10
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• pp.1145-1152
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• 2014

The RFID (Radio-Frequency Identification) system is a technology to discern things by radio and an epoch-making new method to improve product management such as distribution, transport, mobilization, inventory control. However, RFID, which uses radio, is at risk for information leakage and falsification due to the vulnerability of security of the communication section. We designed the new authentication protocol by applying the tent map, which is the representative complex systems, to the RFID communication system. A more solid and simple authentication system was designed by applying the initial value sensitivity and irregularity, which are the representative characteristics of the complex system, to the reader and tag of RFID. The purpose of this paper is to verify the usability of the RFID authentication protocol design that uses the nonlinear system shown in this thesis by the new system differentiated from the authentication system that depends on the existing hash function or random numbers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.4
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• pp.745-751
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• 2012

As disaster number increases, governmental institutions is trying to construct effective disaster information system. Especially, most institutions are using disaster information system based on GIS such as electronic disaster map. However, most previous systems have vulnerability when connecting to the another systems because systems consider only specific area and system is independent data structure. Above all things, existing have to put a lot of time and effort because system need direct work course for service. Therefore, this paper implements quick and methodical disaster information service via study of data code and map, microblog service from internet portal site.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.1
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• pp.117-125
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• 2019

Deep Learning, which is being used in various fields recently, is being threatened with Adversarial Attack. In this paper, we experimentally verify that the classification accuracy is lowered by adversarial samples generated by malicious attackers in image classification models. We used MNIST dataset and measured the detection accuracy by injecting adversarial samples into the Autoencoder classification model and the CNN (Convolution neural network) classification model, which are created using the Tensorflow library and the Pytorch library. Adversarial samples were generated by transforming MNIST test dataset with JSMA(Jacobian-based Saliency Map Attack) and FGSM(Fast Gradient Sign Method). When injected into the classification model, detection accuracy decreased by at least 21.82% up to 39.08%.

• Convergence Security Journal
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• v.20 no.4
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• pp.197-208
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• 2020

Based on the network infrastructure advanced in the information knowledge society, the structure of computer net work is operated by establishing the composition of network in various forms that have secured the security. In case of computer network of national/public organizations, it is necessary to establish the technical and managerial securit y environment even considering the characteristics of each organization and connected organizations. For this, the im portance of basic researches for cyber training by analyzing the technical/managerial vulnerability and cyber threats based on the classification and map of cyber threats according to the characteristics of each organization is rising. T hus, this study aims to analyze each type of external/internal cyber threats to computer network of national/public o rganizations established based on the dualistic infrastructure network of internet and national information network, a nd also to present the cyber threat framework for drawing the elements of cyber security training, by drawing and analyzing the actual elements of cyber threats through the case-based scenario.

• Journal of The Geomorphological Association of Korea
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• v.27 no.3
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• pp.87-103
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• 2020

The purpose of this study is to evaluate the risk of cropland and man-made infrastructures in a landslide-prone area using a GIS-based method. To achieve this goal, a landslide inventory map was prepared based on aerial photograph analysis as well as field observations. A total of 550 landslides have been counted in the entire study area. For model analysis and validation, extracted landslides were randomly selected and divided into two groups. The landslide causative factors such as slope, aspect, curvature, topographic wetness index, elevation, forest type, forest crown density, geology, land-use, soil drainage, and soil texture were used in the analysis. Moreover, to identify the correlation between landslides and causative factors, pixels were divided into several classes and frequency ratio was also extracted. A landslide susceptibility map was constructed using a bayesian predictive model (BPM) based on the entire events. In the cross validation process, the landslide susceptibility map as well as observation data were plotted with a receiver operating characteristic (ROC) curve then the area under the curve (AUC) was calculated and tried to extract a success rate curve. The results showed that, the BPM produced 85.8% accuracy. We believed that the model was acceptable for the landslide susceptibility analysis of the study area. In addition, for risk assessment, monetary value (local) and vulnerability scale were added for each social thematic data layers, which were then converted into US dollar considering landslide occurrence time. Moreover, the total number of the study area pixels and predictive landslide affected pixels were considered for making a probability table. Matching with the affected number, 5,000 landslide pixels were assumed to run for final calculation. Based on the result, cropland showed the estimated total risk as US $ 35.4 million and man-made infrastructure risk amounted to US $ 39.3 million.