• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.911-919
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• 2011

In recent medical analysis, it becomes more important to looking for risk factors related to mental illness. If we find and identify their relevant characteristics of the risk factors, the disease can be prevented in advance. Moreover, the study can be helpful to medical development. These kinds of studies of risk factors for mental illness have mainly been discussed by using the logistic regression model. However in this paper, data mining techniques such as CART, C5.0, logistic, neural networks and Bayesian network were used to search for the risk factors. The Bayesian network of the above data mining methods was selected as most optimal model by applying delirium data. Then, Bayesian network analysis was used to find risk factors and the relationship between the risk factors are identified through a radial graph.

• Proceedings of the Korea Society for Simulation Conference
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• 2000.11a
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• pp.16-21
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• 2000

본 연구는 대형 프로젝트의 위험분석을 위한 확률적 Network 시뮬레이션모델의 연구로서 Simulation방법으로 프로젝트의 성공 및 실패확률을 산정 하였다. 프로젝트의 주요 불확실성 요소(Uncertainty Factors)인 프로젝트의 수행기간(Time), 비용(Cost) 및 성과(Performance) 등의 계획은 실패 없이 추진되어야 하는 것이 중요하다. 연구 개발 및 신기술개발과 같이 대형 프로젝트의 경우, 그 성과 달성의 위험(Risk)성은 매우 크며 이러한 위험 예측 및 분석이 프로젝트의 성공적인 수행을 위하여 매우 중요 시 된다. 본 연구에서는 이를 위한 위험분석(Risk Analysis)의 방법으로 일반적으로 쉽게 사용할 수 있는 위험요인법(Risk Factor Analysis)과 확률적 Network 시뮬레이션모델을 제시하였으며 또한 이를 위한 Simulation프로그램을 개발하였으며 이를 신 기술개발 프로젝트에 응용하는 과정을 보였다. 본 연구에서 개발된 관련 프로그램을 보완 할 경우 대형 프로젝트의 각종 의사결정 시에 매우 유용하게 활용될 수 있으리라 생각된다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.2
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• pp.101-111
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• 2004

Risk analysis process, which identifies vulnerabilities and threat causes of network assets and evaluates expected loss when some of network assets are damaged, is essential for diagnosing ISP network security levels and response planning. However, most existing risk analysis systems provide only methodological analysis procedures, and they can not reflect continually changing vulnerabilities and threats information of individual network system on real time. For this reason, this paper suggests new system design methodology which shows a scheme to collects and analyzes data from network intrusion detection system and vulnerability analysis system and estimate quantitative risk levels. Additionally, experimental performance of proposed system is shown.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.323-333
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• 2011

We analyzed using logistic to find factors with a mental disorder because logistic is the most efficient way assess risk factors. In this paper, we applied data mining techniques that are logistic, neural network, c5.0, cart and Bayesian network to delirium data. The Bayesian network method was chosen as the best model. When delirium data were applied to the Bayesian network, we determined the risk factors associated with delirium as well as identified the network between the risk factors.

• Journal of Navigation and Port Research
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• v.41 no.5
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• pp.287-296
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• 2017

The Formal Safety Assessment (FSA) is a structured and systematic methodology developed by the IMO, aimed at assessing the risk of vessels and recommending the method to control intolerable risks, thereby enhancing maritime safety, including protection of life, health, the marine environment and property, by using risk analysis and cost-benefit assessment. While the FSA has mostly been applied to merchant vessels, it has rarely been applied to a DP vessel, which is one of the special purpose vessels in the offshore industry. Furthermore, most of the FSA has been conducted so far by using the Fault Tree Analysis tool, even though there are many other risk analysis tools. This study carried out the FSA for safe operation of DP vessels by using the Bayesian network, under which conditional probability was examined. This study determined the frequency and severity of DP LOP incidents reported to the IMCA from 2001 to 2010, and obtained the Risk Index by applying the Bayesian network. Then, the Risk Control Options (RCOs) were identified through an expert brainstorming and DP vessel simulations. This study recommends duplication of PRS, regardless of the DP class and PRS type and DP system specific training. Finally, this study verified that the Bayesian network and DP simulator can also serve as an effective tool for FSA implementation.

• Journal of the Korea Society for Simulation
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• v.21 no.4
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• pp.91-102
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• 2012

Network port scan attack is the method for finding ports opening in a local network. Most existing IDSs(intrusion detection system) record the number of packets sent to a system per unit time. If port scan count from a source IP address is higher than certain threshold, it is regarded as a port scan attack. The degree of risk about source IP address performing network port scan attack depends on attack count recorded by IDS. However, the measurement of risk based on the attack count may reduce port scan detection rates due to the increased false negative for slow port scan. This paper proposes a method of summarizing 4 types of information to differentiate network port scan attack more precisely and comprehensively. To integrate the riskiness, we present a risk index that quantifies the risk of port scan attack by using PCA. The proposed detection method using risk index shows superior performance than Snort for the detection of network port scan.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.1789-1794
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• 2014

This paper suggests an application method for a superconducting fault current limiter (SFCL) using an evaluation index to estimate the risk regarding the short-circuit capacity of the circuit breaker (CB). Recently, power distribution systems have become more complex to ensure that supply continuously keeps pace with the growth of demand. However, the mesh or loop network power systems suffer from a problem in which the fault current exceeds the short-circuit capacity of the CBs when a fault occurs. Most case studies on the application of the SFCL have focused on its development and performance in limiting fault current. In this study, an analysis of the application method of an SFCL considering the risk of the CB's short-circuit capacitor was carried out in situations when a fault occurs in a loop network power system, where each line connected with the fault point carries a different current that is above or below the short-circuit capacitor of the CB. A loop network power system using PSCAD/EMTDC was modeled to investigate the risk ratio of the CB and the effect of the SFCL on the reduction of fault current through various case studies. Through the risk evaluations of the simulation results, the estimation of the risk ratio is adequate to apply the SFCL and demonstrate the fault current limiting effect.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 1996.11a
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• pp.65-74
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• 1996

Risk analysis is time-consuming and expensive process〔1〕〔6〕. Automated risk analysis tools have been widely used in industry and government to support decision making process and reduce cost. However, difficulties in materializing impact of threats and fast-changing network environments make analysis process more complicated and less trusted since impacts are relative in network environments. HAWK system is developed to improve the accuracy of analysis result in network-oriented environment. It provides user-friendly environments and considers network environments as primary assets.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.73-78
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• 2024

COVID-19 pandemic outbreak increased the use of Internet of Medical Things (IoMT), but the existing IoMT solutions are not free from attacks. This paper proposes a secure and resilient framework for IoMT, it computes the risk using Risk Impact Parameters (RIP) and Risk is also calculated based upon the Threat Events in the Internet of Medical Things (IoMT). UICC (Universal Integrated Circuit Card) and TPM (Trusted Platform Module) are used to ensure security in IoMT. PILAR Risk Management Tool is used to perform qualitative and quantitative risk analysis. It is designed to support the risk management process along long periods, providing incremental analysis as the safeguards improve.

• Journal of Korea Water Resources Association
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• v.48 no.10
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• pp.781-791
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• 2015

Dam risk analysis requires a systematic process to ensure that hydrologic variables (e.g. precipitation, discharge and water surface level) contribute to each other. However, the existing dam risk approach showed a limitation in assessing the interdependencies across the variables. This study aimed to develop Bayesian network based dam risk analysis model to better characterize the interdependencies. It was found that the proposed model provided advantages which would enable to better identify and understand the interdependencies and uncertainties over dam risk analysis. The proposed model also provided a scenario-based risk evaluation framework which is a function of the failure probability and the consequence. This tool would give dam manager a framework for prioritizing risks more effectively.