• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.6
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• pp.59-69
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• 2005

Ad hoc network is the network which can be considered without a pre-constructed infrastructure, and a mobile node can join the network freely. However, the participation of the mobile nodes to the ad hoc network brings up much burden of re-computation for new routes, because it leads to losing the connection frequently. And, also, it causes serious security problem to be broadcasted wrong information by the malicious user. Therefore, it needs authentication against the mobile nodes. To make that Possible, we have two methods: single CA and distributed CA. In the case of CA method, the wireless network can be collapsed owing to expose the CA, but still the distributed CA method is a little more safe than previous one because it needs attacks toward a lot of CAs to collapse the network We can consider Secret Share scheme as the method that constructs the distributed CA system, but it is weak when the network size is too large. In this paper, we suggest hierarchical structure for the authentication method to solve this problem, and we will show the results of simulation for this suggestion.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.531-540
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• 2021

As cyber attacks and crimes increase exponentially and hacking attacks become more intelligent and advanced, hacking attack methods and routes are evolving unpredictably and in real time. In order to reinforce the enemy's responsiveness, this study aims to propose a method for developing an artificial intelligence-based security control platform by building a next-generation security system using artificial intelligence to respond by self-learning, monitoring abnormal signs and blocking attacks.The artificial intelligence-based security control platform should be developed as the basis for data collection, data analysis, next-generation security system operation, and security system management. Big data base and control system, data collection step through external threat information, data analysis step of pre-processing and formalizing the collected data to perform positive/false detection and abnormal behavior analysis through deep learning-based algorithm, and analyzed data Through the operation of a security system of prevention, control, response, analysis, and organic circulation structure, the next generation security system to increase the scope and speed of handling new threats and to reinforce the identification of normal and abnormal behaviors, and management of the security threat response system, Harmful IP management, detection policy management, security business legal system management. Through this, we are trying to find a way to comprehensively analyze vast amounts of data and to respond preemptively in a short time.

• Knowledge Management Research
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• v.22 no.2
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• pp.227-246
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• 2021

In the context of the global pandemic caused by COVID-19, emergency alert text messages can violate the privacy of confirmed corona positive cases. This study used conjoint analysis to identify the essential information factors and the privacy invasion information factors of local government initiated safety notices. As a result of this study, we found eight essential information factors, including all routes of the confirmed case and ten privacy invasion factors of safety notices. In addition, we found that there is a similarity between the combinations of information perceived to be the most essential and perceived as the most significant privacy invasion; both combinations include the confirmed case's personal and route information. This study ultimately tried to suggest a way to lower the concern about privacy invasion of the confirmed cases without damaging the emergency alert text messages' essential information. We expect that this study will provide researchers and policymakers interested in disaster communication with valuable theoretical and practical implications.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.3
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• pp.149-156
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• 2021

This study collected and analyzed case studies related with the use of spatial information in North Korea to prioritize construction and required supporting processes in order to propose a short-term and long-term road map for the establishment of spatial information in North Korea. Recent research cases related to the prioritization of spatial information development were analyzed, and priority for the construction of infrastructure was derived based on the interconnectedness and relationship of national infrastructure. Due to the inaccessibility and remoteness of North Korea, all of the five studies determined priorities according to questionnaires and consulting of refugees and knowledgeable figures by expert groups. In summary, priority was given to unarmed and transborder areas, major cities, special zones, and development zones, while in terms of facilities, priority was given to power communication, railroads, water and sewage architectural buildings, roads, and dams. In the case of prioritizing the establishment of national infrastructure for the unified Korean Peninsula, the development of major areas, ports, and the related city-level spots to develop a line that promotes the sharing of routes such as transportation networks, water, and energy, thus leading to a scenario involving the development of cotton at an urban and national level.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.4
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• pp.474-482
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• 2021

An average of two to three typhoons that occur in the Philippines or Taiwan pass through Korea each year owing to the influence of the geographical location and western winds. Because Jinhae Bay is known as Korea's representative typhoon refuge, it is filled with ships during typhoons and later becomes saturated with ships anchored to the surrounding routes. If a strong wind drags an anchored ship, a collision accident may occur because of the short distance between the ships. Therefore, a systematic anchoring safety management of Jinhae Bay is required. In this study, the minimum wind speeds of a dragging anchor based on the water depths of Jinhae Bay anchorages were investigated. When 7-9 shackles were given, the minimum wind speeds were 48-63, 46-61, and 39-54 knots at depths of 20, 35, and 50 m, respectively. As the water depth increased, the length of the cable laid on the sea bed became shorter than 5 m owing to the external force, and the minimum wind speed showed a significant difference of 4-8 knots. In addition, ships with high holding power anchors (AC-14 type) had higher minimum wind speeds than ships with conventional anchors (ASS type). Finally, it was confirmed that at a depth of 50 m, dragging easily occurred even when a high holding power anchor was applied.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.627-632
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• 2021

Luxury products are sold in various online shopping malls in China. Companies utilize celebrities as their advertising models or disclose their CSR information to lower perceived risk. This study scrutinized the effects of CSR information and celebrity models on the relationship between perceived risk and the intention to use online shopping malls. According to the elaboration likelihood model, when consumers perceive high risk, they use the central route to process information and form attitudes. Celebrity models and CSR information as secondary clues may not have a significant effect. To test the hypotheses, a 2 (risk H/L)×2 (CSR)×2 (model) factorial design was employed. Study results found in a low perceived risk situation, CSR information or a celebrity model endorsing their products significantly increased the intention to use the shopping mall (model w/ 3.407 vs. w/o 2.88; CSR w/ 3.29 vs. w/o 2.779). However, in a perceived high-risk situation, their effects were not significant. Therefore, it is noteworthy that celebrity models and CSR information are effective in increasing the intention to use online shopping malls only when consumers use peripheral routes in a perceived low-risk situation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.1
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• pp.49-56
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• 2021

The purpose of this study is to develop a methodology to select a cluster of night traffic accidents using CRP (Continuous Risk Profile) analysis. the other purpose of this study is to present the characteristics of the traffic accident cluster section selected at night using CRP analysis. The CRP analysis was performed considering traffic volume of target routes through traffic accident data. In addition, variables were set according to the freeway sections. the method of subtracting the daytime CRP from the nighttime CRP was used to analyze the nighttime traffic accident. As a result, Using the CRP analysis, the sections of hotspot were identified and plotted based on traffic accidents. Also, the sections where traffic accidents are frequent were those where IC or Tunnels were installed, and there was a deviation from the general section. In conclusion, CRP analysis could be used to calculate the frequent section of specialized traffic accidents at night, and it was selected as a point in need of improvement due to the frequent occurrence of specialized traffic accidents at night in the section where IC or tunnel facilities are installed. In addition, it is inferred that the number of specialized traffic accidents at night in the section where IC or tunnel facilities are installed is a factor in the problem of night visibility due to lighting facilities.

• Korean Journal of Environment and Ecology
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• v.35 no.4
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• pp.347-376
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• 2021

Investigating and evaluating regionally distributed plant resources provide fundamental information (inventory) to conserve plant diversity in target areas. Nevertheless, the examination of inventory to collect information in areas with little interest has been insufficient. In this study, the vicinity of Mt. Baegamsan(1,004m) was investigated for plant resources in the central and southern part of the Korean peninsula, which has received low interest. Nine surveys identified a total of 638 taxa consisting of 108 families, 339 genera, 572 species, 12 subspecies, 49 varieties, and 5 forms. One taxon was designated to be the endangered wild plant by the Ministry of Environment, and a total of 29 taxa were designated to be endemic species in Korea. Floristic target species identified by the surveys included 1 taxon for grade V, 13 taxa for grade IV, 36 taxa for grade III, 29s taxa for grade II, and 34 taxa for grade I. A total of 38 taxa were identified to be naturalized plants, and 3 of them were designated as invasive alien plants by the Ministry of Environment. There was a difference in plant distribution between western and eastern areas of Mt. Baegamsan. The endangered and valuable plants for conservation were mainly identified from Mt. Baegamsan peak area, the ridge, and the western area. Considering the plant distribution, the Mt. Baegamsan region, located on Nakdong-jungmaek, was estimated to be dispersal routes for plant expansion and retreat.

• Journal of Environmental Health Sciences
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• v.48 no.2
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• pp.75-85
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• 2022

Background: Various types of semi-volatile organic compounds (SVOCs) exist in the public's living environment. They occur in different forms in terms of their physical and chemical properties and partition coefficients. As a consequence, indoor exposure to SVOCs occurs via various routes, including inhalation of air and airborne particles, skin contact, and dust intake. Objectives: To propose a method for assessing human exposure to the SVOCs occurring in the air of an indoor environment, the concentrations of SVOCs in house dust and organic films measured in a real residential environment were estimated in terms of gas-phase concentration using the partition coefficient. Assessment of inhalation exposure to SVOCs was performed using this method. Methods: Phthalates were collected from samples of house dust and organic films from 110 households in a real residential environment. To perform an exposures assessment of the phthalates present in organic films, gas-phase concentration was calculated using the partition coefficient. The airborne gas-phase concentrations of phthalates from the house dust and organic films were estimated and exposure assessment was performed based on the assumption of inhalation exposure from air. Results: As a result of the exposure assessment for gas-phase phthalates from house dust and organic films, preschool children showed the highest level of inhalation of phthalates, followed by school children, adults, and adolescents. Conclusions: This study includes the limitation of not considering different SVOCs exposure pathways in the health impact assessment, including those of phthalates in the indoor living environment. However, this study has the significance of performing exposure assessment based on exposure to SVOCs present in indoor air that originated from organic films in the indoor residential environment. Therefore, the results of this study should be useful as basic data for exposure and health risk assessments of SVOCs associated with organic films in the indoor environment.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.149-155
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• 2021

In this study, we intend to develop a defective road surface object recognition model that automatically detects road surface defects that restrict the movement of the transportation handicapped using electric mobile devices with deep learning. For this purpose, road surface information was collected from the pedestrian and running routes where the electric mobility aid device is expected to move in five areas within the city of Busan. For data, images were collected by dividing the road surface and surroundings into objects constituting the surroundings. A series of recognition items such as the detection of breakage levels of sidewalk blocks were defined by classifying according to the degree of impeding the movement of the transportation handicapped in traffic from the collected data. A road surface object recognition deep learning model was implemented. In the final stage of the study, the performance verification process of a deep learning model that automatically detects defective road surface objects through model learning and validation after processing, refining, and annotation of image data separated and collected in units of objects through actual driving. proceeded.