• KDI Journal of Economic Policy
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• v.38 no.3
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• pp.53-77
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• 2016

Financial soundness in the household sector matters for financial stability and for the real economy. The level of household debt in Korea raises concern about the financial soundness of the household sector due to its size, growth rate and quality. Against this backdrop, we assess the financial vulnerability of borrowers based on an analysis of credit bureau (CB) data, in which the actual credit activities of most individuals are recorded at a high frequency in Korea. We construct over-indebtedness indicators from the CB data and then assess the predictability of forthcoming defaults. Based on the over-indebtedness indicators, we show how borrowers are distributed in terms of over-indebtedness and how the over-indebted differ from average borrowers in terms of their characteristics. Furthermore, we show how the aggregate credit risk in the household sector would change under macroeconomic distress by analyzing how each borrower's credit quality would be affected by adverse shocks. The findings of this paper may contribute to assessing household debt vulnerability and to enhancing regulatory and supervisory practices for financial stability.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.464-465
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• 2014

Analysis of characteristics in software vulnerabilities can be used to assess security risks and to determine the resources needed to develop patches quickly to handle vulnerability discovered. Being a new research area, the quantitative aspects of software vulnerabilities and risk assessments have not been fully investigated. However, further detailed studies are required related to the security risk assessment, using rigorous analysis of actual data which can assist decision makers to maximize the returns on their security related efforts. In this paper, quantitative software vulnerability analysis has been presented for major Web browsers (Internet Explorer (IE), Firefox (FX), Chrome (CR) and Safari (SF)) with respect to the Common Vulnerability Scoring System (CVSS). The results show that, almost all the time, vulnerabilities are compromised from remote networks with no authentication required systems, and exploitation aftermath is getting worse.

• Management & Information Systems Review
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• v.27
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• pp.149-172
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• 2008

Since the 9/11 terror attack, the event which caused supply chain disruption, supply chain security has becomes more important than ever before. Furthermore, such company's logistics strategies conflicting supply chain security as increased global sourcing, JIT manufacturing are increasing supply chain vulnerability. It could burden for global companies to strengthen supply chain security because not only it requires additional investment cost but also changes of companiy's global logistics strategy. However, on the other hand, supply chain visibility and resilience can be improved through supply chain security. In addition, it allows companies to stabilize supply chain structure as well as rapid and flexible response to market demand. The key issue is balancing between efficiency and supply chain security. To do this, identifying risk elements under the supply chain and assessing vulnerability of each supply chain components should be performed before developing efficient supply chain security management system without obstructing supply chain efficiency.

• The Journal of Information Systems
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• v.17 no.1
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• pp.23-43
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• 2008

Nowadays, openness and accessibility of information systems increase security threats from inside and outside of organization. Appropriate password is supposed to bring out security effects such as preventing misuses and banning illegal users. This study emphasizes on choosing passwords from perspective of information security and investigated user's security awareness affecting behavioral intention. The research model proposed in this study includes user's security belief which is influenced by risk awareness factors such as information assets, threats and vulnerability elements. The risk awareness factors ale derived from risk analysis methodologies for information security. User's risk awareness is a factor influencing the security belief, attitude toward security behavior, and security behavioral intention. According to the result of this study, while vulnerability is not related to the risk awareness, information assets and threats are related to the user's risk awareness. There is a significant relationship between risk awareness and security belief. Also, user's security behavioral intention is significantly affected by security attitude.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.192-194
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• 2015

The growing size and complex process in construction project recently leads to increase risk and the losses as well. Even though researchers have identified the major risk indicators, there is lack of comprehensive and quantitative research for identifying the relationship between the risk indicators and economic losses associated with construction projects. To address this shortage of research, this study defines risk indicators and create a framework to assess the influence of economic losses from the indicators. An insurance company's claim payout record was accepted as the dependent variable to reflect the real economic losses. Based on the claims, we categorized the causes and results of accidents. To establish framework, built environment vulnerability indicators and geographical vulnerability indicators were employed as the risk indicators. A Pearson correlation analysis was adopted to validate the relationship with loss ratio and risk indicators. Consequently, this framework and its results may offer significant references for under writers of insurance companies and loss prevention activities.

• Korea Multimedia Society
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• v.12 no.1
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• pp.32-42
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• 2008

• Journal of Korean Society of Rural Planning
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• v.23 no.3
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• pp.21-36
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• 2017

Climate change is intensifying storms and floods around the world. Where nature has been destroyed by development, communities are at risk from these intensified climate patterns. This study was to suggest a methodology for estimating flood vulnerability using Potential Flood Damage(PFD) concept and classify city/county about Potential Flood Damage(PFD) using various typology techniques. To evaluate the PFD at a spatial resolutions of city/county units, the 20 representative evaluation indexing factors were carefully selected for the three categories such as damage target(FDT), damage potential(FDP) and prevention ability(FPA). The three flood vulnerability indices of FDT, FDP and FPA were applied for the 167 cities and counties in Korea for the pattern classification of potential flood damage. Potential Flood Damage(PFD) was classified by using grouping analysis, decision tree analysis, and cluster analysis, and characteristics of each type were analyzed. It is expected that the suggested PFD can be utilized as the useful flood vulnerability index for more rational and practical risk management plans against flood damage.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.79-92
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• 2020

As the number of systems increases and the network size increases, automated attack prediction systems are urgently needed to respond to cyber attacks. In this study, we developed four types of information gathering sensors for collecting asset and vulnerability information, and developed technology to automatically generate attack graphs and predict attack targets. To improve performance, the attack graph generation method is divided into the reachability calculation process and the vulnerability assignment process. It always keeps up to date by starting calculations whenever asset and vulnerability information changes. In order to improve the accuracy of the attack target prediction, the degree of asset risk and the degree of asset reference are reflected. We refer to CVSS(Common Vulnerability Scoring System) for asset risk, and Google's PageRank algorithm for asset reference. The results of attack target prediction is displayed on the web screen and CyCOP(Cyber Common Operation Picture) to help both analysts and decision makers.

• Structural Engineering and Mechanics
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• v.91 no.3
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• pp.279-289
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• 2024

The purpose of this study is to represent a useful alternative for the preliminary seismic vulnerability assessment of existing reinforced concrete buildings by introducing a statistical approach employing the binary logistic regression technique. Two different predictive statistical models, namely full and reduced models, were generated utilizing building characteristics obtained from the damage database compiled after 1999 Düzce earthquake. Among the inspected building parameters, number of stories, overhang ratio, priority index, soft story index, normalized redundancy ratio and normalized lateral stiffness index were specifically selected as the predictor variables for vulnerability classification. As a result, normalized redundancy ratio and soft story index were identified as the most significant predictors affecting seismic vulnerability in terms of life safety performance level. In conclusion, it is revealed that both models are capable of classifying the set of buildings being severely damaged or collapsed with a balanced accuracy of 73%, hence, both are able to filter out high-priority buildings for life safety performance assessment. Thus, in this study, having the same high accuracy as the full model, the reduced model using fewer predictors is proposed as a simple and viable classifier for determining life safety levels of reinforced concrete buildings in the preliminary seismic risk assessment.

• Journal of the Korean Society of Safety
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• v.31 no.2
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• pp.49-56
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• 2016

In Korea, there exist many mountains, and sudden storms occur during the summer season. When severe rainstorm events occur in steep slope topography, risk of debris flow is increased. Once debris flow occurs in urban area, it may cause casualties and physical damages due to rapid debris flow velocity along a steep slope. Accordingly, preventing method of sediment-related disaster for demage mitigation are essential. Recently, various studies on debris flow have been conducted. However, the prediction of the physical propagation of debris flow along the steep slope was not thoroughly investigated. Debris flow is characterized by various factors such as topography, properties of debris flow, amount of debris flow. In the study the numerical simulation was focused on the topographic factor. Fundamental analysis of the risk area was implemented with emphasis on the propagation length, thickness, and the development of maximum velocity. The proposed results and the methodology of estimating the structural vulnerability would be helpful in predicting the behavior and the risk assessment of debris flow in urban area. These results will be able to estimate the vulnerability of urban areas affected the most damage by debris flow.