• Convergence Security Journal
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• v.20 no.2
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• pp.91-99
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• 2020

The purpose of this study is to present the application of Information and Communication Technology(ICT) during the 4th Industrial Revolution for the efficient implementation of government emergency preparedness policies. Brainstorming by experts categorized the government's emergency preparedness policies into 4 types and 12 detailed tasks. Classification results were used by AHP(Analytic Hierarchy Process) to analyze relative importance and priorities. The AHP survey found that strengthening crisis management responsiveness was the most important detailed task. Artificial Intelligence(AI), Internet of Things(IoT), Unmanned Autonomy System, Virtual Reality(VR), and Augmented Reality(AR) were presented as major information and communication technology(ICT) for the efficient execution of detailed tasks.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.6
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• pp.107-117
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• 2014

The importance of a network security to protect infringement of corporate assets has been issued due to the increasing various threats such as warm virus, vicious codes, and hacking. Thus, the goal of this research is to discover the procedure and methods for a NAC system implementation. In this case study, we suggest that the critical management issues during the implementing a NAC system as well as measure its performance in qualitative and quantitative perspective. The contribution of this paper is both to lead to the further research in this network security field and to provide a guideline for companies willing to introduce a NAC system.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.63-76
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• 2016

Multiperiod portfolio selection problem attracts more and more attentions because it is in accordance with the practical investment decision-making problem. However, the existing literature on this field is almost undertaken by regarding security returns as random variables in the framework of probability theory. Different from these works, we assume that security returns are uncertain variables which may be given by the experts, and take absolute deviation as a risk measure in the framework of uncertainty theory. In this paper, a new multiperiod mean absolute deviation uncertain portfolio selection models is presented by taking transaction costs, borrowing constraints and threshold constraints into account, which an optimal investment policy can be generated to help investors not only achieve an optimal return, but also have a good risk control. Threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Based on uncertain theories, the model is converted to a dynamic optimization problem. Because of the transaction costs, the model is a dynamic optimization problem with path dependence. To solve the new model in general cases, the forward dynamic programming method is presented. In addition, a numerical example is also presented to illustrate the modeling idea and the effectiveness of the designed algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1381-1390
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• 2021

Smart grid is a representative convergence new technology in the era of the 4th industry revolution that deals with three broad security areas consisting of control system, the power grid, and the consumer. As it is a convergence new technology of the 4th industrial society, it is true that it can have a positive effect on the country's technological development, growth engine, and economic feasibility in the future. However, since the smart grid is expected to cause enormous damage in the event of a security accident, energy-related organizations must prepare various security measures to predict and respond to the latest security incidents. In this paper, the current status of domestic and foreign smart grids, trends in security standards, vulnerabilities and threats, and prospects for smart grid security technologies are to be considered.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.2
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• pp.279-287
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• 2022

With the advancement of cyber threats and the development of hacking technologies, cyber security is being emphasized in various fields such as automobiles and ships. According to this trend, various industrial fields are demanding cybersecurity, and related certifications. In this paper, cybersecurity type approval is compared with the RMF stage under the premise that there are common elements with RMF in that cybersecurity elements must be reflected in the entire system development cycle. For comparison, type approval of maritime cyber security of the Korean Register of Shipping was selected. In conclusion, although type approval of maritime cyber security acquisition procedure is not divided by development stage like the RMF, there are the commonalities in the procedure to apply the cybersecurity element to the System development lifecycle like the RMF. Accordingly, the possibility of determining that the cybersecurity element was applied to the entire development cycle was confirmed.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.378-378
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• 2009

본IT와 정보기술의 발달로 삶의 환경은 더욱 편리해지고 첨단화 되어가고 있다. 그중 RFID 기술은 우리가 인지하지 못하고 있는 동안에 생활의 중요한 부분을 차지하고 있으며 그 응용분야는 다양하다. 최근 군에서는 이 RFID를 활용하여 탄약관리와 주둔지 경계, SCM등 단계를 설정하고 군에서 적용할 수 있는 다양한 분야에 적용을 모색하고 있다. 이에 따라 중요성이 강조되고 있는 RFID를 군 유통분야의 콜드체인 시스템 구축을 위한 해결책으로 적용방안과 필요성을 분석한다.

• Proceedings of the KAIS Fall Conference
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• 2006.05a
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• pp.498-501
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• 2006

본 논문에서는 고령화 사회로 진입되고 있는 우리 사회에서 더 한층 관심이 고조되고 있는 의료 서비스를 목표로 하는 U-Health 케어 시스템의 선진국의 사례와 함께 적용 가능한 U-Health 케어 시스템 모델을 제시하였다.

• Proceedings of the KAIS Fall Conference
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• 2010.05b
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• pp.1177-1179
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• 2010

본 연구는 생산 공장, 거점창고, 지역창고, 대리점으로 이어지는 일련의 SCM상에서의 물류센터의 최적의 입지를 선정 문제에 Network Flow Algorithm을 적용하고자 한다. 경로최소화, 전체비용최소화, 손실함수 등의 목적에 따라 문제가 다양하게 있을 수 있다. 최적화 문제에서 대표적으로 사용되는 Maximut flow의 알고리즘을 자세히 알아본다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.10
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• pp.3011-3022
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• 2009

The analytic test results are as follows. This thesis categorized into independent variables, multiple factors, such as asset attributes, cost reduction expectation, corporate IT competence, service qualities, system adequacy, information security, easy system management, uncertain IT, supplier capacity, intra-industry competition. And, this research thesis categorized into moderators, the factor, such as the adequacy between suppliers and customers industries. And, this categorized into dependent variables, multiple factors, such as the effects of ASP introduction. But, it was analyzed that only cost reduction expectation out of independent variables had not positive effects on the effects of ASP introduction. And, it was confirmed that the higher communications between suppliers and customers' industries, and the higher fulfillment of contracts, suppliers' service qualities, and suppliers' cooperation with customers had the adjusting effects on factors of ASP-based introduction.

• Journal of Korean Society for Quality Management
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• v.50 no.3
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• pp.459-471
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• 2022

Purpose: The purpose of this study was to increase prediction accuracy for an anomaly interval identified using an artificial intelligence-based time series anomaly detection technique by establishing a pre-processing process. Methods: Significant variables were extracted by applying feature selection techniques, and anomalies were derived using the TadGAN time series anomaly detection algorithm. After applying machine learning and deep learning methodologies using normal section data (excluding anomaly sections), the explanatory power of the anomaly sections was demonstrated through performance comparison. Results: The results of the machine learning methodology, the performance was the best when SHAP and TadGAN were applied, and the results in the deep learning, the performance was excellent when Chi-square Test and TadGAN were applied. Comparing each performance with the papers applied with a Conventional methodology using the same data, it can be seen that the performance of the MLR was significantly improved to 15%, Random Forest to 24%, XGBoost to 30%, Lasso Regression to 73%, LSTM to 17% and GRU to 19%. Conclusion: Based on the proposed process, when detecting unsupervised learning anomalies of data that are not actually labeled in various fields such as cyber security, financial sector, behavior pattern field, SNS. It is expected to prove the accuracy and explanation of the anomaly detection section and improve the performance of the model.