• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.11C
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• pp.1081-1089
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• 2002

In these days many Organizations recognize risk of information asset by rapid change of information system environments, and need suitable management for that. Also many organization which operate important information-communication infrastructure take interest in threat, vulnerability and risk analysis of important asset by enforcement of Act on protection of information and communication infrastructure. But, it is most that methodology and tools that analyze risk for organization's information asset are developed in abroad up to now, domestic research of this field is insufficient stage. An research of this field is necessary in domestic because it can't reflect domestic actuality by depending on most foreign methodology or a tool. In this paper we proposed design and implementation for the risk analysis methodology, a prototype and important modules that considers the user convenience. We expect that the result of this paper will for step improvement of domestic risk analysis methodology and tool development.

• Information Systems Review
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• v.5 no.2
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• pp.169-182
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• 2003

The growth of electronic commerce make business to business electronic commerce market grow dramatically due to dramatic decrease of transaction cost and increase of productivity. It also influences the way of building transaction relationship between buyers and suppliers. This study tends to prove electronic market theory for Internet based 13213 commerce. We observe and analyze the implementation and usage patterns of procurement system of I company. The result shows that even through Internet enable many buyers and suppliers to participate and transact each other, the transaction pattern is different according to asset specificity and uncertainty as follows. First, with adoption of internet, the product with the higher asset specificity rather than lower asset specificity can be easily purchased. Second, Internet doesn't make any significant influence on the transaction of the product with higher uncertainty. But, organization's pre-audit process can indirectly influence on the decrease of the transaction uncertainty.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.6
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• pp.807-816
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• 2018

Threat hunting is defined as a process of proactively and iteratively searching through networks to detect and isolate advanced threats that evade existing security solutions. The main concept of threat hunting is to find out weak points and remedy them before actual cyber threat has occurred. And HMM(Hunting Maturity Matrix) is suggested to evolve hunting processes with five levels, therefore, CSOC(Cyber Security Operations Center) can refer HMM how to make them safer from complicated and organized cyber attacks. We are developing a system for cyber situation awareness system with pro-active threat hunting process called unMazeTM. With this unMaze, it can be upgraded CSOC's HMM level from initial level to basic level. CSOC with unMaze do threat hunting process not only detecting existing cyber equipment post-actively, but also proactively detecting cyber threat by fusing and analyzing cyber asset data and threat intelligence.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.419-430
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• 2023

Currently, NFTs have no dominant application except for the proof of ownership for digital content, and it also have small liquidity problem, which makes their price difficult to predict. Real estate usually has very high barriers to investment due to its high pricing. Real estate can be converted into NFTs and also divided into small value fungible tokens (FTs), and it can increase the the volume of the investor community due to more liquidity and better accessibility. In this document, we implement and design a system that allows ordinary users can invest on high priced real estate utilizing Black Litterman (BL) model-based Portfolio investment interface. To this end, we target a set of real estates pegged as collateral and issue NFT for the collateral using blockchain. We use oracle to get the current real estate information and to monitor varying real estate prices. After tokenizing real estate into NFTs, we divide the NFTs into easily accessible price FTs, thereby, we can lower prices and provide large liquidity with price volatility limited. In addition, we also implemented BL based asset portfolio interface for effective portfolio composition for investing in multiple of real estates with small investments. Using BL model, investors can fix the asset portfolio. We implemented the whole system using Solidity smart contracts on Flask web framework with public data portals as oracle interfaces.

• The Korean Journal of Archival Studies
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• no.70
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• pp.5-40
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• 2021

Administrative information dataset records produced by various systems designed for work are difficult to manage on a case-by-case basis, requiring separate procedures to identify and evaluate data-sets. Identified data set records are apprasal and transferred to the records management system or disposed of. In this process, sufficient records management elements must be reflected in the production system itself in order to adhere to the principles of record management. In this paper, the functional requirements of the production system to accurately identify and safely manage data-sets were derived and applied based on the case of the KR property management system. It is hoped that this research on functional requirements of production systems will be added to lead to the creation of standards for functional requirements of data set production systems.

• The Journal of Society for e-Business Studies
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• v.18 no.4
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• pp.215-240
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• 2013

This research has reviewed the major composition concepts and the positive research results in the selected studies which were theoretically based on IDT (Innovation Diffusion Theory), IRM (Model of Innovation Resistance), TAM(Technology Acceptance Model), and IAPA(Information Asset Protection Activity) in order to improve the theoretical explanation of major characterized factors influencing on the introduction of MST (Mobile Security Technology). The characterized factors for the adaptation of MST and 17 hypotheses on the MST study models in order to test the effects on the intention to use are empirically verified by utilizing the analysis method of structure equation model. As a result of a study, First, the most influential characterized factors of IRM are shown as compatibility, complexity, relative advantage, information asset protection in order. Second, the characterized factors affecting intention to use are shown as relative advantage, compatibility, innovation resistance, performance expectancy. The results of this study are relevantly significant to establish the theoretical foundation of the study on the adaptation of MST and The verification of the characterized factors provide strategic implication for the introduction of MST and policy direction which alleviates informational gap between new MST and previous Security Technology to diffusion agency.

• Management & Information Systems Review
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• v.33 no.1
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• pp.45-63
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• 2014

A trading system is a computer trading program that automatically submits trades to an exchange. Mechanical a trading system to execute trade is spreading in the stock market. However, a trading system to trade a single asset might occur instability of the profit because payoff of this system is determined a asset movement. Therefore, it is necessary to develop a trading system that is trade two assets such as a pair trading that is to sell overvalued assets and buy the undervalued ones. The aim of this study is to propose a relative value based trading system designed to yield stable and profitable profits regardless of market conditions. In fact, we propose a procedure for building a trading system that is based on the rough set analysis of indicators derived from a price ratio between two assets. KOSPI 200 index futures and S&P 500 index futures are used as a data for evaluation of the proposed trading system. We intend to examine the usefulness of this model through an empirical study.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.3
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• pp.67-77
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• 2019

The purpose of this study is to introduce a town management system that utilizes private sectors and public space resources in urban management area. In this study, we are studying 7 town management districts in Japan which have been establishing diverse management systems that are propelled by the private sectors and private fund. We analyzed qualitative characteristics of 7 town management districts by surveying the operating status of organization, financial management and activities. Through the analysis, we clarified their characteristics that are related to establishing background. Also, we suggested conclusions of the study as follows: First of all, it is important to develop a town management method that takes into account the characteristics of the target district in order to overcome the limitation of applying uniform method and increase sustainability and efficiency of privately-led urban management. Second, marketing and promotion are critical strategies in town management since they are satisfying both private and public benefits. The high rate of reinvestment in marketing and promotions shows efforts to maintain the asset value of the private sector and continue to revitalize the city. Finally, in order to carry out urban management with private initiative, it is necessary to establish a working organization capable of realizing the operational direction of the steering committee to secure the executive power.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.720-724
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• 2008

Concentration about value of invisible asset has increased in the condition of rapid business circumstance change. As one of these concentration, many company adopted knowledge management, and construction industry also tried to adopt knowledge management. However, it is difficult for construction company to get expected effects because of knowledge management system in no relation with business process. To solve this problems, this study adopted BPM that has many functions, such as business process design, operation, monitoring, sustainable improvement, to knowledge classification structure.