• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.193-202
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• 2020

This study was intended to present the magnitude of privacy infringement concerns and their relationship to consumer innovation (functional innovation, hedonistic innovation, social innovation, cognitive innovation), to identify differences among groups and to suggest implications for marketing strategies for the spread of new products. The implications of this study are as follows. First, functional innovation has shown that differences exist between groups. Analysts say that sensitive groups are buying products that can simplify their work immediately after release despite concerns over privacy violations. Second, hedonistic innovation has shown that differences exist between groups. These findings suggest that sensitive groups prefer novel products, products that give excitement and excitement about products, and products that give new enjoyment and fun that they have never known before. Third, social innovation has been shown that there is no difference between groups. These analyses show that the self-esteem of using products that others have never experienced before, and the curiosity that anyone envies, are purchased or used first. Finally, cognitive innovation showed that differences existed between groups. These analyses show that new products are purchased when they meet the functions, design, and innovation that consumers want.

• The Journal of Society for e-Business Studies
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• v.12 no.4
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• pp.37-51
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• 2007

As the highly improved Internet and information technology has led to the diversification of users' demands, personalization service attract lots of attention as a means to meet highly diversified demand of users. However, personalization service costs a lot. Also concerns over a possible violation of privacy have been raised since the service uses technology to find out the users' profiles. This research studies the advantages individuals acquire from personalization service and how privacy concern influences service acceptance. Research on related documents and information gathering from e-commerce sites derived six representative types of service. Questionnaires were utilized to research privacy concern according to services, service usefulness, and service acceptance. As expected, privacy concern has a negative relation to acceptance while service usefulness has a positive relation to it, thereby resulting in an offset between two variables. Moreover, they play a different role depending on what kinds of service or in formation should be provided. The results derived from this paper will help the e-commerce sites provide personalization service by collecting personal information while protecting users' privacy.

• Informatization Policy
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• v.29 no.1
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• pp.60-83
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• 2022

The purpose of this study is to empirically analyze the effect of individual perception of artificial intelligence and the level of digital literacy on the acceptance of artificial intelligence-based public services. For empirical analysis, a research model was set up based on the technology acceptance model and planned behavior theory using survey data of 2017 and analyzed through structural equations. To summarize the results of the analysis, firstly, the positive perception of individuals about artificial intelligence technology plays a role in reinforcing attitudes toward benefits and reducing concerns about public service in which artificial intelligence technology has been introduced. Secondly, the level of digital literacy reinforces both benefits and concerns about artificial intelligence technology, but it was found that the intention to use public services was reinforced through the benefits of artificial intelligence technology perceived by individuals, rather than privacy concerns about artificial intelligence technology. Thirdly, it was confirmed that the perceived benefits of individuals on artificial intelligence technology reinforced the intention to use public civil services, and privacy concerns negatively influenced the intention to use. It was confirmed that the influence of a perceived ease of use and usefulness, as opposed to privacy concerns, further reinforces the intention to use. Both citizens' positive perceptions regarding the accuracy and reliability of information provided through artificial intelligence technology and institutional complementation of responsibility for errors caused by artificial intelligence technology are strengthened, and technical problems related to privacy protection are solved.

• Journal of Digital Convergence
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• v.13 no.4
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• pp.219-225
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• 2015

There has been an exponential growth in the distribution and possession of sensitive information because of the emergence of various information channels such as smart devices, social media, etc. This enables the internet based web or mobile service operation institutions collecting the more personal information with ease, and in turn causes the issues of the privacy concerns. Followings are the results of this study: First, the information privacy concern has the negative effects upon the trust. Second, the information privacy concern has the negative effects upon the provision intention of personal information and the trust has positive effects upon the offering intention of personal information. At last, the offering intention of the personal information has the positive effects upon the behavior to provide the personal information.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.6
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• pp.197-208
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• 2014

In an information society, privacy protection is one of the most important ethical issues. In medical institutes in which personal medical information is collected and stored, in addition, a privacy breach can cause a serious damage on personal lives. This study attempted to develop privacy concern measurement tool in personal medical information to measure patients' concern on their medical information from medical service consumers' perspective and verify its validity. For this, privacy concern measurement tool in personal medical information was developed based on the results of previous studies. After performing Exploratory Factor Analysis(EFA) and Confirmatory Factor Analysis(CFA) on the measurement tool, its reliability and validity were verified. It appears that the measurement tool would be useful in developing decent privacy protection policy after investigating citizens' concern on the protection of personal medical information and domains they are interested in. For medical institutes as well, they would be helpful in coming up with a reasonable plan after figuring out problems in the protection of personal medical information and current status.

• Knowledge Management Research
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• v.22 no.2
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• pp.227-246
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• 2021

In the context of the global pandemic caused by COVID-19, emergency alert text messages can violate the privacy of confirmed corona positive cases. This study used conjoint analysis to identify the essential information factors and the privacy invasion information factors of local government initiated safety notices. As a result of this study, we found eight essential information factors, including all routes of the confirmed case and ten privacy invasion factors of safety notices. In addition, we found that there is a similarity between the combinations of information perceived to be the most essential and perceived as the most significant privacy invasion; both combinations include the confirmed case's personal and route information. This study ultimately tried to suggest a way to lower the concern about privacy invasion of the confirmed cases without damaging the emergency alert text messages' essential information. We expect that this study will provide researchers and policymakers interested in disaster communication with valuable theoretical and practical implications.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.165-184
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• 2023

Recently, Deep learning analysis of unstructured text data using language models, such as Google's BERT and OpenAI's GPT has shown remarkable results in various applications. Most language models are used to learn generalized linguistic information from pre-training data and then update their weights for downstream tasks through a fine-tuning process. However, some concerns have been raised that privacy may be violated in the process of using these language models, i.e., data privacy may be violated when data owner provides large amounts of data to the model owner to perform fine-tuning of the language model. Conversely, when the model owner discloses the entire model to the data owner, the structure and weights of the model are disclosed, which may violate the privacy of the model. The concept of offsite tuning has been recently proposed to perform fine-tuning of language models while protecting privacy in such situations. But the study has a limitation that it does not provide a concrete way to apply the proposed methodology to text classification models. In this study, we propose a concrete method to apply offsite tuning with an additional classifier to protect the privacy of the model and data when performing multi-classification fine-tuning on Korean documents. To evaluate the performance of the proposed methodology, we conducted experiments on about 200,000 Korean documents from five major fields, ICT, electrical, electronic, mechanical, and medical, provided by AIHub, and found that the proposed plug-in model outperforms the zero-shot model and the offsite model in terms of classification accuracy.

• Convergence Security Journal
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• v.14 no.2
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• pp.73-79
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• 2014

In the 21st century, the higher CCTV, hidden Camera, and surveillance and contra-surveillance in Cyber-space are, the higher the voices of concern about surveillance society nationally are. Nevertheless, phenomenon of panoptisme is becoming into general use. Actually, this watching system should be on the rise but this is the output playing up and advertising the positive effect of immediate convenience and offering safety that government and business made. Thus, this study wants to offer implication to warn the invasion of privacy and generalization controlled society as pointed out cause and problem of the surveillance society time according to the digital era.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06c
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• pp.307-309
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• 2006

유비쿼터스 컴퓨팅 패러다임이 제시된 이래로 세계적으로 유비쿼터스 컴퓨팅에 대한 연구가 활발히 진행되고있다. 그러나 아직까지 유비쿼터스 컴퓨팅은 현실세계에 적용하기에는 많은 기술적. 비기술적 장벽들이 많이 존재한다. 보안과 프라이버시에 관한 사회적인 우려는 유비쿼터스 컴퓨팅 기술의 실제 환경에 적용하는데 큰 걸림돌로 작용한다. 따라서 진행되고 있는 많은 유비쿼터스 연구들은 각각의 프로젝트에 적합한 보안 및 프라이버시 보호를 위한 기술들을 개발하여 적용하고 있는 실정이다. 유비쿼터스 시스템 연구센터는 유비쿼터스 컴퓨팅을 구현하기 위해 커뮤니티 컴퓨팅을 제안하였다. 커뮤니티 컴퓨팅에서 발생할 수 있는 보안 문제점들을 해결하기 위해 커뮤니티 스킨을 구현하였다. 커뮤니티 스킨은 커뮤니티 구성원들을 커뮤니티 외부 개체들과 구분 짓고, 외부의 침입으로부터 보호해 줄 수 있다. 커뮤니티 스킨은 암호학적 알고리즘을 적용함으로써 구현될 수 있다. 본고에서는 보안 서비스를 4가지 유형으로 분류하고 이를 토대로 커뮤니티가 보안 협약을 통한 커뮤니티 스킨을 형성 하도록 하였다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.3
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• pp.503-512
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• 2020

The revisions to data privacy acts allows the disclosure of data after anonymizing personal information. Such anonymized data is expected to be useful in research and services, but there are high concerns about privacy breaches such as re-identifying of the individuals from the anonymized data. In this paper, we showed that identifying individuals from public data is not very difficult, and also raises questions about the reliability of the public data. We suggest that users understand the trade-offs between data disclosure and privacy protection so that they can use data securely under the revised data privacy acts.