• Journal of The Korean Association of Information Education
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• v.14 no.3
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• pp.365-373
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• 2010

It is required that public schools in information society should act as a balancer between the equal educational opportunity and development of the personal capacity. However, public schools have faced a situation to be blamed and praised by social parties concerned from the point of view of educational excellence. The aim of this study is to suggest some conceptual ideas for sharing & delivery system of educational information, which is based on the paradigm of web 2.0 characterized as participation, sharing, and openness. To do it, we analyzed the recent technological trends and took a group discussion with leading teachers in educational information.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.75-84
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• 2017

As there has been growing interests in PHR-based personalized health management project, various institutions recently explore safe methods of recording personal medical and health information. In particular, innovative medical solution can be realized when medical researchers and medical service institutes can generally get access to patient data. As EMR data is extremely sensitive, there has been no progress in clinical information exchange. Moreover, patients cannot get access to their own health data and exchange it with researchers or service institutions. It can be operated in terms of technology, yet policy environment are affected by state laws as well as Privacy and Security Policy. Blockchain technology-independent, in transaction, and under test-is introduced in the medical industry in order to settle these problems. In other words, medical organizations can grant preliminary approval on patient information exchange by using the safely encrypted and distributed Blockchain ledger and can be managed independently and completely by individuals. More apparently, medical researchers can gain access to information, thereby contributing to the scientific advance in rare diseases or minor groups in the world. In this paper, we focused on how to manage personal medical information and its protective use and proposes medical treatment exchange system for patients based on a permissioned Blockchain network for the safe PHR operation. Trusted Model for Sharing Medical Data (TMSMD), that is proposed model, is based on exchanging information as patients rely on hospitals as well as among hospitals. And introduce medical treatment exchange system for patients based on a permissioned Blockchain network. This system is a model that encrypts and records patients' medical information by using this permissioned Blockchain and further enhances the security due to its restricted counterfeit. This provides service to share medical information uploaded on the permissioned Blockchain to approved users through role-based access control. In addition, this paper presents methods with smart contracts if medical institutions request patient information complying with domestic laws by using the distributed Blockchain ledger and eventually granting preliminary approval for sharing information. This service will provide an independent information transaction and the Blockchain technology under test will be adopted in the medical industry.

• Asia pacific journal of information systems
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• v.29 no.2
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• pp.308-327
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• 2019

The concept of sharing economy has received rich attention in recent years. As a typical type of business model in the sharing economy, online short rent has been paid attention by both industry and academia. In this study, we find trust to be a critical determinant to the success of online short rent platforms. Based on three dimensions of trust theory, i.e., ability, benevolence and integrity, we investigate the factors influencing tenant' willingness to participate in online short rent. We further examine the extent to which trust can influence the number of sales and comments of rooms listed at online short-term rent platforms, which can represent tenant' willingness to participate in the sharing economy. The results show that the trust dimensions represented by a landlord's personal characteristics have significant positive correlations with the number of sales and comments. For example, the real name authentication and the sesame score can represent the trust integrity; online replay ratio and the average confirmation time representing the trust sincerity, and the order acceptance ratio representing the trust ability. On this basis, we proposed some recommendations for both platforms and landlords. For example, the landlords can improve the tenants' trust by authenticating his/her real name, replying actively and timely. For platforms, when they make housing list ranking rules, they can take the landlord's personal attributes that may affect trust into consideration. Moreover, platforms can also allow landlords to supply value-added services to improve service quality and ultimately promote the virtuous circle of the platform ecosphere. Through conducting the empirical research on a particular application of the sharing economy, we aim to fill the research gap of this field in China and provide theoretical and practical contributions to the future development of online short rent.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.56-66
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• 2023

The goal of deep learning is to extract complex features from multidimensional data use the features to create models that connect input and output. Deep learning is a process of learning nonlinear features and functions from complex data, and the user data that is employed to train deep learning models has become the focus of privacy concerns. Companies that collect user's sensitive personal information, such as users' images and voices, own this data for indefinite period of times. Users cannot delete their personal information, and they cannot limit the purposes for which the data is used. The study has designed a deep learning method that employs privacy protection technology that uses distributed collaborative learning so that multiple participants can use neural network models collaboratively without sharing the input datasets. To prevent direct leaks of personal information, participants are not shown the training datasets during the model training process, unlike traditional deep learning so that the personal information in the data can be protected. The study used a method that can selectively share subsets via an optimization algorithm that is based on modified distributed stochastic gradient descent, and the result showed that it was possible to learn with improved learning accuracy while protecting personal information.

• Knowledge Management Research
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• v.9 no.2
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• pp.63-86
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• 2008

Knowledge management system(KMS) was introduced into the company in order to apply knowledge management. But according to KMS is changed into information management system, the company is considered Community in Practice(CoP) instead of KMS. Because within CoP, individuals can interact with one another to solve problems, test new ideas, learn about new developments in their field and build a sense of affiliation with others in similar circumstances. In spite of it's importance there is few empirical study about CoP. So the purpose of this study is to examine which personal characteristics influence knowledge sharing and which context factors(including structural and relational characteristics) moderate relationship between individual characteristics and knowledge sharing within CoP through empirical study.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.286-288
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• 2000

최근 웹에 대한 관심이 집중되면서 정보의 양이 지수적으로 증가하고 있다. 웹 사용자들은 정보 검색에 있어서 많은 어려움을 겪게 되었다. 이 문제를 해결하기 위해 정보검색(Information Retrieval) 시스템의 웹 환경으로의 적용이나 개인 적응형 에이전트(Personal Adaptive Agent)를 이용한 정보 여과(Information Filtering)에 대한 연구가 진행되어왔다. 본 논문에서는 BISAgent(Bookmark Information sharing Agent) 시스템이 사용자에게 효과적인 정보 검색을 제공함을 설명한다. BISAgent는 여러 사용자의 북마크 정보를 공유하여 협동적 정보 여과기법(Collaborative Filtering)을 이용한 협동적 웹 브라우징(Collaborative Web Browsing)을 수행한다. 이 시스템의 성능을 평가하기 위해 검색 결과의 개수를 통한 정보 여과의 양적 측면과 통계적 방법을 이용하여 정보 추천(information recommendation)의 정확성을 실험하였다.

• Journal of Korea Trade
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• v.23 no.7
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• pp.45-63
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• 2019

Purpose - This study aims to examine the factors that affect consumers' intention to use a global business-to-consumer sharing platform. Design/methodology - The questionnaire collected 300 copies from June 25 to July 11, 2019, of which 281 were used for statistical processing. The structural equation model (SEM) was used to test hypothesis in this research. Findings - The results showed that information innovation, personalization, and personal innovation influenced perceived usefulness, and social connectivity did not affect perceived usefulness. And perceived usefulness greatly influenced the intention to use. Research limitations/implications - The limitations of the study are that most of the survey respondents were in their twenties and could not grasp the perception of sharing economy services for various age groups. This paper derived implications that sharing platform promotes sharing and cooperation, which are the basic principles of international trade, to increase the intrinsic value of resources by cyclically using and utilizing limited resources around the world. Originality/value - It aims to contribute to the growth of consumer value-related industries and the welfare of society by providing implications from the point of view of sharing platform services.

• Journal of the Korea Society of Computer and Information
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• v.21 no.10
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• pp.43-48
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• 2016

This study is to examine how big data collects user's information and is used; the status quo of exposures of user's information, and various measures of self-control by the user. This study is also to look their ethical issues and discuss problems of privacy concerning big data. As a way for users to self-control their information, they need to check the log-in state of web portal sites and set up their account so that customized advertisement and location information cannot be tracked. When posting a blog, the value of posting should be controlled. When becoming a member of a web site, users must check the access terms before agreement and beware of chained agreements and/or membership joins in order to control the exposure of their personal information. To prevent information abuse through big data through which user's information is collected and analyzed, all users must have the right to control, block or allow personal information. For an individual to have the right to control over his information, users must understand the concept of user's information and practice ethics accompanied by newly given roles in the Internet space, which will lead to the establishment of the sound and mature information society on the Internet.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.1
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• pp.53-63
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• 2011

An SNS(Social Network Service) enables people to form a social network on online as in the real world. With the rising popularity of the service, side effects of SNSs were issued. Therefore we propose and implement a policy-based privacy protection module and access control policy language for ensuring the right of control of personal information and sharing data among SNSs. The policy language for protecting privacy is based on an attribute-based access control model which grants an access to personal information based on a user's attributes. The policy language and the privacy protection module proposed to give the right of control of personal information to the owner, they can be adopted to other application domains in which privacy protection is needed as well as secure sharing data among SNSs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.750-753
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• 2017

Recently, the processing and utilization of big data, which is generated by the spread of smartphone, SNS, and the internet of things, is emerging as a new growth engine of ICT field. However, in order to utilize such big data, De-identification of personal information should be done. De-identification removes identifying information from a data set so that individual data cannot be linked with specific individuals. De-identification can reduce the privacy risk associated with collecting, processing, archiving, distributing or publishing information, thus it attempts to balance the contradictory goals of using and sharing personal information while protecting privacy. De-identified information has also been re-identified and has been controversial for the protection of personal information, but the number of instances where personal information such as big data is de-identified and processed is increasing. In addition, many de-identification guidelines have been introduced and a method for de-identification of personal information has been proposed. Therefore, in this study, we describe the big data de-identification process and follow-up management, and then compare and analyze de-identification methods. Finally we provide personal information protection issues and solutions.