• Journal of Multimedia Information System
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• 제5권2호
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• pp.99-104
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• 2018

Phishing website has become a crucial concern in cyber security applications. It is performed by fraudulently deceiving users with the aim of obtaining their sensitive information such as bank account information, credit card, username, and password. The threat has led to huge losses to online retailers, e-business platform, financial institutions, and to name but a few. One way to build anti-phishing detection mechanism is to construct classification algorithm based on machine learning techniques. The objective of this paper is to compare different classifier ensemble approaches, i.e. random forest, rotation forest, gradient boosted machine, and extreme gradient boosting against single classifiers, i.e. decision tree, classification and regression tree, and credal decision tree in the case of website phishing. Area under ROC curve (AUC) is employed as a performance metric, whilst statistical tests are used as baseline indicator of significance evaluation among classifiers. The paper contributes the existing literature on making a benchmark of classifier ensembles for web phishing detection.

• The Journal of Asian Finance, Economics and Business
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• 제7권7호
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• pp.85-93
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• 2020

In peer-to-peer (P2P) loan markets, as most lenders are unskilled and inexperienced ordinary individuals, it is important to know the characteristics of borrowers that significantly impact their repayment performance. This study investigates the effects and importance of borrowers' past repayment performance track record within the platform to identify its predictive power. To this end, I analyze the detailed loan repayment data from two leading P2P lending platforms in Korea using a Cox proportional hazard, multiple linear regression, and logit models. Furthermore, the predictive power of the factors proxied by borrowers' track records are evaluated through the receiver operating characteristic (ROC) curves. As a result, it is found that the borrowers' past track record within the platform have the most important impact on the repayment performance of their current loans. In addition, this study also reveals that the borrowers' track record is much more predictive of their repayment performance than any other factor. The findings of this study emphasize that individual lenders must take into account the quality of borrowers' past transaction history when making a funding decision, and that platform operators should actively share the borrowers' past records within the markets with lenders.

• International Journal of Naval Architecture and Ocean Engineering
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• 제6권3호
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• pp.670-684
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• 2014

Ship Information Systems (SISs) have been one of the main research focuses in ship design and become a multidisciplinary area. With these growing research trends, it is important to consolidate the latest knowledge and information to keep up with the research needs. In this paper, the SIS and its different forms are introduced and discussed. The beginning of this paper discusses the history and evolution of SIS. The next part of this paper focuses on different fields and research areas such as networking technology, information fusion, information decision, message display, ship control in real-time SISs. A Semi-Physical Simulation Platform (SPSIM) designed for SIS research and its running effect through a new Fuzzy-PID fusion algorithm are introduced in this paper then. A brief literature survey and possible future direction concerning each topic is included.

• 한국빅데이터학회지
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• 제7권2호
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• pp.139-152
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• 2022

플랜트를 대상으로 하는 엔지니어링의 업무영역은 플랜트의 기획, 설계, 시공, 운영 및 폐기에 이르는 생애주기에 걸친 생산성과 성능 및 품질에 직접적인 영향을 미치는 복합적인 기술분야이다. 이때 발생하는 다양한 유형의 데이터를 활용하여 의사결정을 활용하는 것은 후속 과정뿐만 아니라 생애주기 관점에서도 중요한 영향을 미치고 있다. 하지만 이러한 데이터를 통합적으로 관리하고 분석할 수 있는 시스템은 부족하다. 본 논문에서는 플랜트 생애주기에서 발생하는 데이터를 관리하고 활용할 수 있는 지식베이스 기반 플랜트 엔지니어링 분석 플랫폼을 개발하였다. 플랫폼에서는 기수집된 엔지니어링 데이터를 전처리한 지식베이스를 제공하고, 이를 레퍼런스 데이터로 AI 모델에 활용하도록 분석 기능과 시각화를 제공한다. 사용자는 플랫폼을 통한 선행기술과 축적된 지식의 활용을 통해 데이터 분석을 진행하고 시각화를 의사결정에 활용해 경험에만 의존하던 공사를 합리적이고 체계적으로 관리할 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권3호
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• pp.974-992
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• 2021

Recently, the healthcare field has undergone rapid changes owing to the accumulation of health big data and the development of machine learning. Data mining research in the field of healthcare has different characteristics from those of other data analyses, such as the structural complexity of the medical data, requirement for medical expertise, and security of personal medical information. Various methods have been implemented to address these issues, including the machine learning model and cloud platform. However, the machine learning model presents the problem of opaque result interpretation, and the cloud platform requires more in-depth research on security and efficiency. To address these issues, this paper presents a recent technology for Internet-of-Things-based (IoT-based) health big data processing. We present a cloud-based IoT health platform and health big data processing technology that reduces the medical data management costs and enhances safety. We also present a data mining technology for health-risk prediction, which is the core of healthcare. Finally, we propose a study using explainable artificial intelligence that enhances the reliability and transparency of the decision-making system, which is called the black box model owing to its lack of transparency.

• Journal of Platform Technology
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• 제9권4호
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• pp.32-41
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• 2021

유럽연합은 자국민의 개인정보보호를 위해 강력한 규제 법령으로 GDPR을 2018년 5월 25일 시행하였다. 글로벌 경제 시대에서 유럽시장 진출 기업에서는 GDPR 대응은 꼭 필요한 선결과제이다. 본 논문에서는 유럽 연합내 거주민의 개인정보 역외 이전을 위한 적절한 수준의 보호조치 대응을 위해 기업에서 준비해야 할 단계별 추진과제를 살펴보았다. 제3국에서의 GDPR 대응은 개별 기업 또는 정부차원의 대응을 할수 있으며, 정부차원의 적정성 결정시 기업의 혜택과 기대효과에 대해서 탐색해 보았다. 적정성 결정 국가의 기업에서는 EU 진출시에 프로세스 간소화, 비용 절감 등의 혜택과 유출사고 대응시 정부차원의 독립된 감독기구 지원으로 인한 부담감 해소 등에 따른 시사점이 있다. 그러나, 적정성 결정 이후에도 기업은 GDPR 원칙, 의무규제 준수를 통한 개인정보보호체계 확보 활동은 지속적으로 필요하며, GDPR 대응 과제에 대한 중요도 변화에 대해서도 유럽 국가와의 계약서 체결을 제외한 대부분 준수되어야 할 과제로 유지가 필요하며, GDPRR 대상 기업들의 차별화된 관리 방안 구축도 기대한다.

• 경영정보학연구
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• 제25권2호
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• pp.31-56
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• 2023

코로나19 펜데믹이 장기화되면서 비대면 업무가 늘어나고 단순반복적인 질문 및 업무에 대한 자동화 수요가 증가하였으며 성과도 보고 있다. 따라서 기업은 더 나아가 E2E 업무에 복잡한 여러 업무 프로세스를 연계하고 위해 AI 등 다양한 기술을 적용하여 모든 작업을 자동화하려고 시도하고 자동화 업무영역을 확장하고 있다. 하지만 Intelligent Process Automation(IPA)부분으로의 확장은 아직 적용사례 및 관련 솔루션을 찾아보기 어려울 정도로 시작 단계에 머물고 있어 복잡하고 다양한 업무 프로세스들로 구성되어 있는 전사업무의 자동화를 고려하고 있는 기업에서는 도입에 대한 의사결정을 내리기에는 부족한 면이 있다. 본 연구에서는 이를 해결하기 위하여 RPA, Chatbot, AI 기술을 적용한 Hyperautomation Platform(HAP) 구성을 제안하였고, HAP를 사용하여 지능형 프로세스 자동화를 가져올 수 있는 적용방안과 현업 업무에 적용 가능한 구현사례를 제시하여 객관적이고 종합적으로 도입을 검토할 수 있도록 하였으며, Hyperautomation 개념의 실현 가능성을 확인하여 HAP를 적극적으로 활용할 수 있도록 하는데 의미와 가치가 있다.

• 한국IT서비스학회지
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• 제1권1호
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• pp.17-27
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• 2002

Buyer-carts to support the purchasing process in the B2B EC platform, can be categorized as s-cart, i-cart, and b-cart depending upon its residing sites : seller, intermediary, and buyer sites. In this paper, after proposing the desired features of buyer-carts in B2B EC as identification, collection, trashing, ordering, payment, tracking, recording, purchasing decision support, and transmission of records to e-procurement systems, we try to analyze each buyer-cart qualitatively from such viewpoints. Moreover, we propose an efficiency evaluation model for quantitative analysis. By setting variables from interview of employees in 30 listed companies In Korea, we try to evaluate the efficiency of buyer-carts in B2B EC. From this paper, we show that the b-cart platform is more efficient than other buyer-carts especially in B2B EC.

• Agricultural and Biosystems Engineering
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• 제5권1호
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• pp.1-4
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• 2004

Community-based precision farming is a new concept of agricultural systems, which leads to organize groups of wise farmers and technology platforms in Japan. The wisdom farmers create a rational farming system to manage hierarchical variability: variability in farmers' community as well as variability of within-field and between-field. The technology platform develops and provides three key-technologies: mapping technology, variable-rate technology, and decision support systems available for rural constraints. Advancement of bio-production robots leads precision farming to the next level, where two technological innovations: how to produce and manage information-oriented fields and information-added products, can be attained.

• Asia pacific journal of information systems
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• 제31권4호
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• pp.575-581
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• 2021

In this opinion article, we review the current streams of the information systems (IS) literature on crowdfunding and discuss how the literature has contributed to expanding our understanding of crowdfunding. Reflecting on the review, we propose avenues for future research to expand the existing knowledge on this impactful topic for the benefit of researchers and practitioners.