• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.15
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• pp.239-261
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• 2001

There are many kinds of risk in int'l trade by internet network, such as credit risk, mercantile risk, contingency risk, exchange risk, physical risk and the risk on internet network. Especially, risk management against credit risk and the risk on internet network are very important. The former is conventional but more important these days. The latter is a new risk that has been incurred owing to the int'l trade by internet network. The system of risk management against the former are firstly, to surely research credit of counterpart by internet, secondly, to certify the entity by password or fingerprint, thirdly, to pay the price under a letter of credit, fourthly, to use the system of int'l trade such as bolero, trade card, finally, to use the authority of electronic trade services. The system of risk management against the latter are firstly, to install the firewall on the own computer network, secondly, to entrust the management own computer network to the network security services firm, thirdly, to electronically communicate with counterpart through the certification authority, finally, to insure against the own network risk with the security insurance company.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1920-1937
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• 2015

Network environment has been under constant threat from both malicious attackers and inherent vulnerabilities of network infrastructure. Existence of such threats calls for exhaustive vulnerability analyzing to guarantee a secure system. However, due to the diversity of security hazards, analysts have to select from massive alternative hardening strategies, which is laborious and time-consuming. In this paper, we develop an approach to seek for possible hardening strategies and prioritize them to help security analysts to handle the optimal ones. In particular, we apply a Risk Flow Attack Graph (RFAG) to represent network situation and attack scenarios, and analyze them to measure network risk. We also employ a multi-objective genetic algorithm to infer the priority of hardening strategies automatically. Finally, we present some numerical results to show the performance of prioritizing strategies by network risk and hardening cost and illustrate the application of optimal hardening strategy set in typical cases. Our novel approach provides a promising new direction for network and vulnerability analysis to take proper precautions to reduce network risk.

• Journal of Navigation and Port Research
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• v.47 no.2
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• pp.93-99
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• 2023

This study aimed to determine relationships among risk factors influencing container port operation using Bayesian network. Risk factors identified from prior studies were classified into five groups: human error, machinery error, environmental risk, security risk, and natural disasters. P anel experts discussed identified risk factors to fulfil conditional probability tables of the interdependence model. The interdependence model was also validated by sensitivity analysis and provided an interrelation of factors influencing the direction of each other. Results of the interdependence model were partially in line with results from prior studies while practices in the global port industry confirmed interrelationships of risk factors. In addition, the relationship between top-ranked risk factors can provide a schematic drawing of the model. Accordingly, results of this study can expand the prior research in the Korean port industry, which may help port authorities improve risk management and reduce losses from the risk.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4531-4544
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• 2021

Because the traditional network information security vulnerability risk assessment method does not set the weight, it is easy for security personnel to fail to evaluate the value of information security vulnerability risk according to the calculation value of network centrality, resulting in poor evaluation effect. Therefore, based on the network security data element feature system, this study designed a quantitative assessment method of network information security vulnerability detection risk under single transmission state. In the case of single transmission state, the multi-dimensional analysis of network information security vulnerability is carried out by using the analysis model. On this basis, the weight is set, and the intrinsic attribute value of information security vulnerability is quantified by using the qualitative method. In order to comprehensively evaluate information security vulnerability, the efficacy coefficient method is used to transform information security vulnerability associated risk, and the information security vulnerability risk value is obtained, so as to realize the quantitative evaluation of network information security vulnerability detection under single transmission state. The calculated values of network centrality of the traditional method and the proposed method are tested respectively, and the evaluation of the two methods is evaluated according to the calculated results. The experimental results show that the proposed method can be used to calculate the network centrality value in the complex information security vulnerability space network, and the output evaluation result has a high signal-to-noise ratio, and the evaluation effect is obviously better than the traditional method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.2
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• pp.87-95
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• 2011

A Renewable Portfolio Standard(RPS) is a regulation that requires the increased generation of energy from renewable energy sources such as solar, wind, fuel cell, small hydro, biomass and geothermal. By environmental, technical and these regulatory reasons, the amount of renewable energy sources will be increased in a network. However, it is hard to assess risk of a transmission network with large scale renewable energy sources because the output characteristics of renewable energies are intermittent. This paper evaluates effects of a transmission system with supplemental large scale renewable energies into the existing system. To evaluate these effects, a methodology for risk level of components in a network is proposed considering steady state and contingency N-1 in this paper. We consider line current and bus voltage in each state of a network.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.6
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• pp.752-757
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• 2014

This paper attempts to evaluate the impact of power plant penetration on constraints of a transmission network and proposes a methodology based on risk level, which can evaluate the condition of the network and facilities intuitionally. Furthermore, based on this methodology, RLII(Risk Level Improvement Index) is proposed in order to establish comprehensive TNEP(Transmission Network Expansion Planning) from a viewpoint of ISO(Independent System Operator). In order to verify the proposed methods in this paper, real power systems in Incheon and Shiheung areas, south Korea are applied to the case study.

• Journal of the Korean Society of Safety
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• v.29 no.1
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• pp.1-6
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• 2014

With increasing number of citizen using subway stations everyday, safety, health and comfort of passengers and occupants became an important social issue. Considering the fact that various physical variables and pollutants are related to indoor air quality (IAQ) which may cause health problem, IAQ need to be closely monitored and controlled in multiple locations in subway stations. This study is a continuation of the previous studies and delay induced in wireless-wired network is experimentally evaluated and the risk involved is assessed. In doing that, a key parameter is identified to be the network delay in different network media. Application of information-theoretic measure to assess the risk in network delay is then discussed. The idea is based on the general principles of engineering design and their applications to quantification of uncertainty in network delay. Experimental results show that more risk is involved in wireless data communication. Efficient and fast conversion of transmission data in both LonWorks/IP server and ZL converter is also noted.

• Journal of Contemporary Eastern Asia
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• v.18 no.1
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• pp.189-216
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• 2019

The frequent occurrence of overwhelming disasters necessitates risk communication systems capable of operating effectively in disaster contexts. Few studies have examined risk communication networks during disasters through social networking services (SNS). This study therefore investigates the patterns of risk communication by comparing Korean and international networks based on the social amplification of risk communication in the context of the Sewol ferry disaster (SFD). In addition, differences in language use and patterns between Korean and international contexts are identified through a semantic analysis using KrKwick, NodeXL, and UCINET. The SFD refers to the sinking of the ferry while carrying 476 people, mostly secondary school students. The results for interpersonal risk communication reveal that the structure of the Korean risk communication network differed from that of the international network. The Korean network was more fragmented, and its clustering was more sparsely knitted based on the impact and physical proximity of the disaster. Semantic networks imply that the physical distance from the disaster affected the content of risk communication, as well as the network pattern.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.23
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• pp.10539-10542
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• 2015

A method to predict the risk of lung cancer is proposed, based on two feature selection algorithms: Fisher and ReliefF, and BP Neural Networks. An appropriate quantity of risk factors was chosen for lung cancer risk prediction. The process featured two steps, firstly choosing the risk factors by combining two feature selection algorithms, then providing the predictive value by neural network. Based on the method framework, an algorithm LCRP (lung cancer risk prediction) is presented, to reduce the amount of risk factors collected in practical applications. The proposed method is suitable for health monitoring and self-testing. Experiments showed it can actually provide satisfactory accuracy under low dimensions of risk factors.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.4
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• pp.997-1006
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• 2015

This study analyzed urban infrastructure risk to flooding based on the possibility map of flooding calculated by neural network model focusing on Seoul. This study found that Gangnam-gu, Songpa-gu, Seocho-gu and Seodaemun-gu contained relatively large high-risk areas to flooding. Over $4.17km^2$ of transportation facilities were located in high-risk area to flooding and Gangnam-gu included over $0.85km^2$ of infrastructures exposed to high inundation risk. This study is meaningful in that it first applied the neural network modeling to flooding risk assesment and results of risk assessment can be incorporated into various planning process.