• Journal of Digital Convergence
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• v.16 no.1
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• pp.217-229
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• 2018

Electronic Health Record (EHR) systems are widely adopted worldwide in hospitals for generating and exchanging records of patient information. Recent developments are moving towards implementing interoperable EHR systems that enable information to be shared seamlessly across healthcare organizations. In this context, this paper explores the factors that cause medical information privacy concerns, identifies how people react to privacy invasion and what their perceptions are towards the acceptance of the EHR system. Interviews were conducted to draw a grounded theory on medical information privacy concerns in the use of EHRs. Medical information privacy concerns are caused by perceived sensitivity of medical information and the weaknesses in security technologies. Trust in medical professionals, medical institutions and technologies plays an important role in determining people's reaction to privacy invasion and their perceptions on the use of EHRs.

• Digital Contents
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• no.10 s.17
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• pp.46-53
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• 1994

• 정보보호뉴스
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• s.133
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• pp.19-21
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• 2008

• Information Systems Review
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• v.24 no.3
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• pp.69-91
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• 2022

The video recommendation services help to save the user's information search time in the overflowing online information, and algorithms for more efficient and accurate recommendation are continuously developed. In particular, TikTok has the largest number of users in the short video industry due to its unique recommendation algorithms. In this study, by applying a privacy calculation model, the research tried to compare users' responses to each type of TikTok's recommendation service. Users are well aware of the privacy concerns and benefits of TikTok's recommendation service. Although there is a risk, it was found that users continue to use TikTok's recommendation service because the benefits are greater.

• Convergence Security Journal
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• v.21 no.3
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• pp.49-56
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• 2021

Recently, artificial intelligence is regarded as an essential technology in our society. In particular, the invasion of privacy in artificial intelligence has become a serious problem in modern society. Split learning, proposed at MIT in 2019 for privacy protection, is a type of federated learning technique that does not share any raw data. In this study, we studied a safe and accurate segmentation learning model using known differential privacy to safely manage data. In addition, we trained SVHN and GTSRB on a split learning model to which 15 different types of differential privacy are applied, and checked whether the learning is stable. By conducting a learning data extraction attack, a differential privacy budget that prevents attacks is quantitatively derived through MSE.

• Journal of Digital Convergence
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• v.11 no.1
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• pp.107-119
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• 2013

The purpose of this study is to find an answer why internet users are unconcern about their privacy information. We found that perceived privacy risk and website usability have a significant effect on privacy unconcern. That is, individuals who have experiences privacy incidents are more likely to be unconcern about their privacy information. Accordingly, organizations who supply services on the web have to pay more attention to these individuals to increase a privacy concern. Implications and Conclusions are discussed.

• Journal of the Korean Society for information Management
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• v.32 no.1
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• pp.63-84
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• 2015

Library users must provide their personal information to libraries. This study surveyed these library users' perception of privacy and the effect of the education after providing library user privacy education. As a result, first, it was found that after education, users were more interested in their privacy, rated the problem of library user privacy as more severe, and rated library user data collection as more likely to be considered privacy invasion. Second, we investigated users' perception of how much user service records being collected in libraries violate users' privacy, which showed a great perception change in 25 questions after the education. Third, in the survey about library and librarians' efforts for protecting library user privacy, it was found that all 15 questions were rated as significantly more important after education. Fourth, library users have recognized that is necessary to process and handle the library record and are more sympathetic to the need for this procedure. Fifth, library users felt the possibility of a library record leak was a very serious threat.

• Knowledge Management Research
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• v.16 no.3
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• pp.23-40
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• 2015

Despite much interest and investment in the Internet of Things (IoT) which expand the Internet to a ubiquitous network including objects in the physical world, there is growing concerns of privacy protections. Because the risk of privacy invasion is higher in IoT environments than ever before, privacy need to be a key issue in the diffusion of IoT. Considering that the privacy concern is a critical barrier for user to adopt information technologies, it is important to investigate users' privacy concerns related to IoT applications. From the triad perspective (i.e., risk on technology, risk on service provider, and trust on legislation), this study aims to examine users' privacy concerns in the context of activity trackers.

• Annual Conference of KIPS
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• 2006.05a
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• pp.951-954
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• 2006

RFID시스템은 태그와 리더, 백엔드DB로 구성되는 무선인식시스템으로 용도와 기능, 크기에 따라 다양하지만 가장 널리 사용될 것으로 예상되는 것은 저가 수동형 태그로 향후 바코드시스템을 대체할 것으로 기대된다. 이러한 RFID시스템은 적법한 리더와 태그에게 정보를 전달해서 도청자로부터 통신을 방해받지 않아야 하고, 원하지 않는 태그 정보의 노출로 인한 개인 프라이버시 침해를 방지할 수 있어야 한다. 본 논문에서는 불특정다수가 이용하는 많은 양의 아이템을 취급하는 공공도서관에서 RFID시스템을 도입함에 따라 예상되는 개인 프라이버시 침해를 방지하기 위해 보안 요구사항을 만족하면서 시스템 사용 환경에 맞는 프라이버시 보호 방식을 제안한다.

• Review of KIISC
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• v.26 no.6
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• pp.30-35
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• 2016

미래인터넷 기술의 하나인 정보 중심 네트워킹은 기존의 호스트 중심 네트워킹 개념을 대체하는 새로운 통신 방식으로, 인터넷과 같은 현재의 통신 방식의 한계를 극복하기 위한 대안으로 제안되었다. 정보 중심 네트워킹은 정보의 근원지 주소가 아닌 정보의 이름을 기반으로 통신하여, 네트워크의 확장성을 높이고 정보의 전송 효율을 높이는 것을 주요 목표로 한다. 이를 위하여 이름 기반 라우팅이나 네트워크 내 캐싱 기능 등을 제공하고, 신뢰성 있는 정보 제공을 위하여 무결성 보장 기능도 제공한다. 이와 같이 설계에서부터 네트워크의 효율과 신뢰성 제공을 고려하여 설계된 네트워킹 개념이지만, 여전히 보안 위협이나 프라이버시 침해 위험이 존재한다. 본 고에서는 정보 중심 네트워킹 구조에서 발생 가능한 보안 위협과 프라이버시 침해에 대응하기 위한 기존의 연구들을 소개하고, 향후 연구 방향을 제시하고자 한다.