• The Journal of Information Systems
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• v.28 no.3
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• pp.39-58
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• 2019

Purpose A digital twin is a digital replication of a physical system. Gartner identified the digital twin as one of the Gartner Top 10 Strategic Technology Trend for three years from 2017. The rapid development of the digital twin market is expected to bring about innovation and change throughout society, and much research has been done recently in academia. In this research, we tried to explore the main research trends for digital twin research. Design/methodology/approach We collected the digital twin research from Web of Science, and analyzed 804 articles that was published during time span of 2010-2018. A total of 41 key authors were selected based on the frequency of citation. We created a co-citation matrix for the core authors, and performed multivariate analysis such as cluster analysis and multidimensional scaling. We also conducted social network analysis to find the influential researchers in digital twin research. Findings We identified four major sub- areas of digital twin research: "Infrastructure", "Prospects and Challenges", "Security", and "Smart Manufacturing". We also identified the most influential researchers in digital twin research: Lee EA, Rajkumar R, Wan J, Karnouskos S, Kim K, and Cardenas AA. Limitation and further research suggestion were also discussed as a concluding remarks.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.217-232
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• 2019

Currently, the crew working on a ship is required to carry a seafarer's book in most countries around the world, including the Republic of Korea (ROK). Yet, many fishermen working in the international waters of the ROK do not abide by this rule as the procedure of obtaining it is rather inconvenient or they do not understand the necessity or the benefits of having it. Also, as the regulation of carrying the certificate has been strengthened, it is important for them to avoid making a criminal record unintentionally. This study discusses the digitalization of the seafarer's book based on several security measures in addition to BLE Beacon-based positioning technology, which can be useful for the e-Navigation. Normally, seamen's certificates are recorded by the captain, medical institution, or issuing authority and then kept in an onboard safe or a certificate cabinet. The material of the certificates is a cloth that can withstand salinity as the certificate could be contaminated by mold. In the past, the captains and their crews were uncooperative when the ROK's maritime police tried to inspect several ships simultaneously because of the time and cost involved. Thus, a system with which the maritime police will be able to conveniently manage the crews is proposed.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.122-130
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• 2021

This study is about an Artificial Intelligence-based fake news identification system and its methods to determine the authenticity of content distributed over the Internet. Among the news we encounter is news that an individual or organization intentionally writes something that is not true to achieve a particular purpose, so-called fake news. In this study, we intend to design a system that uses Artificial Intelligence techniques to identify fake content that exists within the news. The proposed identification model will propose a method of extracting multiple unit factors from the target content. Through this, attempts will be made to classify unit factors into different types. In addition, the design of the preprocessing process will be carried out to parse only the necessary information by analyzing the unit factor. Based on these results, we will design the part where the unit fact is analyzed using the deep learning prediction model as a predetermined unit. The model will also include a design for a database that determines the degree of fake news in the target content and stores the information in the identified unit factor through the analyzed unit factor.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4224-4243
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• 2021

Cognitive radio (CR) is a feasible intelligent technology and can be used as an effective solution to spectrum scarcity and underutilization. As the key function of CR, cooperative spectrum sensing (CSS) is able to effectively prevent the harmful interference with primary users (PUs) and identify the available spectrum resources by exploiting the spatial diversity of multiple secondary users (SUs). However, the open nature of the cognitive radio networks (CRNs) framework makes CSS face many security threats, such as, the malicious user (MU) launches Byzantine attack to undermine CRNs. For this aim, we make an in-depth analysis of the motive and purpose from the MU's perspective in the interweave CR system, aiming to provide the future guideline for defense strategies. First, we formulate a dynamic Byzantine attack model by analyzing Byzantine behaviors in the process of CSS. On the basis of this, we further make an investigation on the condition of making the fusion center (FC) blind when the fusion rule is unknown for the MU. Moreover, the throughput and interference to the primary network are taken into consideration to evaluate the impact of Byzantine attack on the interweave CR system, and then analyze the optimal strategy of Byzantine attack when the fusion rule is known. Finally, theoretical proofs and simulation results verify the correctness and effectiveness of analyses about the impact of Byzantine attack strategy on the throughput and interference.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.115-129
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• 2022

Adopting Internet of Things (IoT)-based technologies in smart homes helps users analyze home appliances electricity consumption for better overall cost monitoring. The IoT application like smart home system (SHS) could suffer from large missing values gaps due to several factors such as security attacks, sensor faults, or connection errors. In this paper, a novel framework has been proposed to predict large gaps of missing values from the SHS home appliances electricity consumption time-series datasets. The framework follows a series of steps to detect, predict and reconstruct the input time-series datasets of missing values. A hybrid convolutional neural network-long short term memory (CNN-LSTM) neural network used to forecast large missing values gaps. A comparative experiment has been conducted to evaluate the performance of hybrid CNN-LSTM with its single variant CNN and LSTM in forecasting missing values. The experimental results indicate a performance superiority of the CNN-LSTM model over the single CNN and LSTM neural networks.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.12-14
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• 2022

One of the most negative social changes of the last decade is population aging which leads to 19 times more patients with Mild Cognitive Disorder(MCI). It is well established that MCI is the most important state that can prevent dementia with early diagnosis and intervention. However, the social security system for patients with dementia is not working properly due to the coronavirus pandemic and the limited human power. This article proposes design principles for dementia training programs of extended reality devices. and The findings in this study provide a guide for considering the cognitive and physical and social functions of patients.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.239-250
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• 2022

A business's Enterprise Resource Planning (ERP) solution is software that fully integrates the services that businesses require, continuously updates business processes and department operations in real-time, and so aids in the successful management of enterprise resources. Previously, ERP solutions were often deployed for large enterprises, but along with the strong digital transformation process, many small and medium enterprises have been deploying Cloud ERP (CERP) solutions. The objective of the study is to measure the factors affecting the successful implementation of CERP solutions at small and medium enterprises and the impact of successful implementation of CERP solutions on business process re-engineering and enterprise performance. Using a quantitative method based on data collected from 230 small and medium enterprises in Vietnam that have been implementing CERP solutions, the results show that there are 5 factors affecting, which are Organizational ERP Strategic, Top management Commitment, Data Security, Training in ERP Projects, Organizational Culture. Research results also show that Successful implementation of CERP has a direct impact on business process re-engineering and business performance. Based on the results, the study has made a number of policy implications in the successful implementation of CERP towards re-engineering business processes to improve the performance of small and medium enterprises.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.47-52
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• 2024

Through the coronavirus pandemic, research on the use and advancement of blockchain-based decentralized identity authentication (Decentralized ID) technology is being actively conducted in various fields, centered on the central government, local governments, and private businesses. In this paper, we introduce the results of development based on Hyperledger Fabric to change the existing central server-based identity authentication to a decentralized one. These development results can strengthen the security and transparency of identity authentication systems for commercial purposes and provide stable services for user ID issuance, inquiry, and disposal. In addition, the decentralized identity authentication system verified performance results of DID creation of 262,000 rps and DID inquiry of 1,850 rps, DID VP creation of 200 rps, and DID VP inquiry of 220 rps or less through public authentication.

• Annual Conference of KIPS
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• 2024.05a
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• pp.505-508
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• 2024

금융산업의 디지털 전환은 사용자에게 편리함을 제공하지만 기존에 존재하지 않던 보안상 취약점을 유발했다. 이러한 문제를 해결하기 위해 기계학습 기술을 적용한 사기 거래 탐지 시스템에 대한 연구가 활발하게 이루어지고 있다. 하지만 모델 학습 과정에서 발생하는 데이터 불균형 문제로 인해 오랜 시간이 소요되고 탐지 성능이 저하되는 문제가 있다. 본 논문에서는 실시간 데이터 오버 샘플링을 통해 이상 거래 탐지 시 데이터 불균형 문제를 해결하고 모델 학습 시간을 개선한 새로운 이상 거래 탐지 시스템(Fraud Detection System, FDS)을 제안한다. 본 논문에서 제안하는 SMOTE(Synthetic Minority Oversampling Technique)를 적용한 LSTM(Long-Short Term Memory) 알고리즘 기반의 FDS 프레임워크는 종래의 LSTM 알고리즘 기반의 FDS 모델과 비교했을 때, 데이터 사이즈가 96.5% 감소했으며, 정밀도, 재현율, F1-Score 가 34.81%, 11.14%, 22.51% 개선되었다.

• Journal of the Korean Society for information Management
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• v.19 no.1
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• pp.23-46
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• 2002

With explosively increasing digital contents, library and Information center should have a new role between knowledge providers and knowledge users as information brokering organization. Electronic transaction system should be required for performing this brokering service since economic value is added to information and knowledge in information society. The developments and changes around library are keeping up with increasing building digital library and digitalizing printed sources. With the rapidly changing circumstances, the Internet is currently witnessing an explosive growth. By serving as a virtual information resource. the Internet can dramatically change the way business is conducted and Information is provided. However because of features o( the Internet like openness and information sharing, it has fundamental vulnerabilities in security issues. For Instance, disclosure of private information and line eavesdropping such as password, banking account, transaction data on network and so on are primary obstruction factors to activation of digital contents delivery on network. For high network security and authentication, this paper looks at smart card technologies and proposes multi-authentication protocol based on smart card on open network, implements and analyzes it.