• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.366-368
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• 2022

지구온난화에 따른 우리나라 주변 환경의 변화와 최근 중국 불법 어선의 연근해 어업 자원의 고갈 등으로 인해 우리나라 연근해 어족자원을 보호할 필요성이 증대되고 있으며, 지속 가능한 어업을 위해서는 어획물의 종류와 양을 정확히 파악하고 불법 어업에 대한 철저한 감시 및 관리가 필요하다. 이러한 시공간적으로 다양하게 변하는 생태 및 어장 환경 정보와 선박에 대한 정보를 통해 해양관측과 위성 원격탐사를 동시에 이용함으로써 근해와 원양 생물자원 실태를 관측하는 것이 가능하다. 본 연구에서는 NOAA-20 위성의 VIIRS (Visible Infrared Imaging Radiometer Suite) DNB (Day & Night Band) 영상을 기반으로 추정한 야간 불빛 자료를 활용하고자 한다. DNB 불빛 영상은 낮은 조도의 불빛을 감지하여 그 정보를 보여 준다. 야간 불빛 자료에 포함된 구름 부분을 마스킹하기 위해 NASA의 신규알고리즘이 적용된JPSS-JRR-CloudMask 기술을 이용하였다. 이번 연구에서는 구름의 영향이 없는 날짜를 선별한 후 AIS 정보에서 어선의 정보를 추출하여 검증 자료로 사용하였다. 실제 선박의 정보를 이용한 위성 불빛 자료의 검증을 통해 위성자료의 신뢰성을 확보하고 향후 불빛과 선단 규모의 상관관계 분석 및 어선의 분포 경향 분석을 통하여 우리나라의 어장환경 분석에 활용 가능할 것으로 기대한다.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.432-436
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• 2023

초거대언어모델(LLM)의 도래에 따라 다양한 과업들이 도메인 관계 없이 제로샷으로 추론이 가능해짐에 따라서 LLM이 다양한 산업분야에 적용되고 있다. 대표적으로 ChatGPT와 GPT-4는 상용 API로 서비스를 제공하여 용이한 서비스 접근으로 다양한 이용층을 끌어들이고 있다. 그러나 현재 상용 API로 제공되고 있는 ChatGPT 및 GPT-4는 사용자의 대화 내역 데이터를 수집해 기업의 보안 문제를 야기할 수 있고 또한 생성된 결과물의 환각 문제로 인한 기업 문서의 신뢰성 저하를 초래할 수 있다. 특히 LLM 생성 글은 인간의 글과 유사한 수준으로 유창성을 확보한만큼 산업현장에서 LLM 작성 글이 판별되지 못할 경우 기업 활동에 큰 제약을 줄 수 있다. 그러나 현재 한국어 LLM 작성 글 탐지 서비스가 전무한 실정이다. 본 논문에서는 한국어 초거대언어모델 작성 글 판별기: KoCheckGPT 를 제안한다.KoCheckGPT는 산업현장에서 자주 사용되는 문어체, 개조식 글쓰기로 작성된 문서 도메인을 목표로 하여 글 전체와 문장 단위의 판별 정보를 결합하여 주어진 문서의 LLM 작성 여부를 효과적으로 판별한다. 다국어 LLM 작성 글 판별기 ZeroGPT와의 비교 실험 결과 KoCheckGPT는 우수한 한국어 LLM 작성 글 탐지 성능을 보였다.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.73-80
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• 2023

In this paper, a technology to protect important information from access in order to revitalize the cloud service market. A technology is proposed to solve the risk of leakage of important confidential and personal information stored in cloud systems, which is one of the various obstacles to the cloud service market. To protect important information, access control rights to cloud resources are granted to cloud service providers and general users. The system administrator has superuser authority to maintain and manage the system. Client computing services are managed by an external cloud service provider, and information is also stored in an external system. To protect important in-house information within the company, all users, it was designed to provide access authority with users including cloud service providers, only after they are authenticated. It is expected that the confidentiality of cloud computing resources and service reliability achieved through the proposed access control technology will contribute to revitalizing the cloud service market.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.947-960
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• 2023

In Korea, traditional paper promissory notes are currently undergoing a transformation, being gradually replaced by electronic notes. This transformation is being steered under the Korea Financial Telecommunications Institute, a trusted authority. However, existing electronic systems have security vulnerabilities, including the risk of hacking and internal errors within the institute. To this end, we have defined a novel anonymous electronic promissory note system based on blockchain. We have constructed a concrete protocol and conducted security analysis of our protocol. Note that, in our protocol, every note information is committed so that the note remains undisclosed until the point of payment. Once the note information becomes public on the blockchain, it enables the detection of illicit activities, such as money laundering and tax evasion. Furthermore, our protocol incorporates a feature of split endorsement, which is a crucial functionality permitted by the Korean electronic note system. Consequently, our proposed protocol is suitable for practical applications in financial transactions.

• Journal of the Korea Society for Simulation
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• v.32 no.4
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• pp.59-67
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• 2023

Private blockchains can apply enhanced security policies that allow only authorized users to participate in the blockchain network. In addition, when used in a career management system where the validity of an individual's career is important, it has the suitable characteristics in terms of information integrity. However, due to the excessive performance requirements of blockchain technology, identifying performance characteristics through simulation can be helpful in stable operation of the system. This paper presents research results that utilized performance evaluation results while constructing a career management system based on the Ethereum blockchain. The service not only serves as a portfolio that records personal career development activities, certification acquisition, and award results, but also provides a community function for career planning to strengthen employment competitiveness. In addition, we present how a compensation policy can be executed to encourage users to participate in career development through community activities. In particular, an appropriate compensation policy was derived by reviewing changes in performance characteristics in accordance with the transaction volume on Geth nodes.

• Advanced Industrial SCIence
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• v.3 no.2
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• pp.17-22
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• 2024

Recently, as the ICT field has been used in various environments, it has become possible to analyze pests by crops, use robots when harvesting crops, and predict by big data by utilizing ICT technologies in a sustainable agricultural environment. However, in a sustainable agricultural environment, efforts to solve resource depletion, agricultural population decline, poverty increase, and environmental destruction are constantly being demanded. This paper proposes an artificial intelligence-based big data processing analysis method to reduce the production cost and increase the efficiency of crops based on a sustainable agricultural environment. The proposed technique strengthens the security and reliability of data by processing big data of crops combined with AI, and enables better decision-making and business value extraction. It can lead to innovative changes in various industries and fields and promote the development of data-oriented business models. During the experiment, the proposed technique gave an accurate answer to only a small amount of data, and at a farm site where it is difficult to tag the correct answer one by one, the performance similar to that of learning with a large amount of correct answer data (with an error rate within 0.05) was found.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.77-87
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• 2024

In this paper, we propose a study applying the Delphi technique to domestic blockchain experts to determine urgent and pivotal conditions for NFT proliferation. We examine these conditions from a PEST (Political, Economic, Social, and Technological Analysis of the Macro Environment) perspective, as well as the functions of digital assets (measurement, storage, and exchange). Through two rounds of expert surveys on the seven NFT perspectives, we identify 6 activating factors that can help guide future policy-making for the NFT market. These factors have broad implications for the development of new industries using blockchain technology and tokens. The Delphi method employed in this study is a group discussion technique that gathers opinions from experts anonymously through two rounds and to address drawbacks related to expert selection bias and opinion alignment, additional opinion collection and review of projections were conducted in each round.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.177-184
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• 2024

In the situation of increasing data at fast speed, we use all kinds of complex ensemble and deep learning algorithms to get the highest accuracy. It's sometimes questionable how these models predict, classify, recognize, and track unknown data. Accomplishing this technique and more has been and would be the goal of intensive research and development in the data science community. A variety of reasons, such as lack of data, imbalanced data, biased data can impact the decision rendered by the learning models. Many models are gaining traction for such interpretations. Now, LIME and SHAP are commonly used, in which are two state of the art open source explainable techniques. However, their outputs represent some different results. In this context, this study introduces a coupling technique of LIME and Shap, and demonstrates analysis possibilities on the decisions made by LightGBM and Keras models in classifying a transaction for fraudulence on the IEEE CIS dataset.

• Asia-Pacific Journal of Business
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• v.14 no.4
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• pp.49-65
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• 2023

Purpose - In the Korean and Chinese social landscape, it is vital to appreciate the significance of the Japanese history problem. The current study investigated whether the perception of the Japanese history problem affects decisions regarding technology adoption in organizations by comparing South Korea and China. Design/methodology/approach - The study involved 305 Korean and 379 Chinese participants who responded to scenarios and surveys regarding the adoption of workplace surveillance cameras supplied by a Japanese company. Findings - Using a moderated mediation model based on protection motivation theory (PMT), we found that past experiences of privacy invasion significantly reduced trust in the adoption of surveillance cameras at work. This relationship was mediated by respondents' perceptions of security vulnerability. The current study, however, did not confirm any significant moderating effect of the Japanese history problem priming on trust in the adoption of workplace surveillance cameras. Research implications - This suggests that the Japanese history problem may have a limited impact on organizational technology adoption decisions, different from the political consumerism behavior driven by public anti-Japanese affectivity. The current study reaffirms the validity and applicability of PMT and provides both theoretical insights and practical recommendations.

• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.283-311
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• 2024

This study examined the factors affecting the intention of the public to share electronic medical records(EMR) based on the theory of reasoned action and the privacy calculus model. It also investigated whether the purpose of EMR sharing varies depending on personal characteristics, such as the degree of interest in health and personal medical history. According to an online survey of 145 people, altruistic enjoyment, awareness of personal information protection, recognition of legal and institutional roles, and interest in health had a positive impact on the level of EMR sharing, and trust in hospitals positively adjusted the relationship between recognition of legal and institutional roles and sharing intentions. Accordingly, we confirmed that the public recognized the role of the government and hospitals in the sharing process as necessary. The public interest benefits of sharing are critical to activating public participation in the sharing of EMR, and it is also essential to prepare guidelines that legally guarantee the security and proper use of EMR.