• Journal of Korea Society of Industrial Information Systems
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• v.22 no.1
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• pp.69-87
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• 2017

This Research Attempted to Clarify the Eeffect of Privacy Concern and Institutional Trust on Privacy Decision based on Privacy Calculus Perspective. We Developed a Research Model Suggesting that the Influence of Privacy Benefit and Privacy risk on the Information Disclosure Behavior and the Influence of Privacy Concern and Institutional Trust on the Privacy Calculus. In this Regard, in Order to Examine the Difference According to the Target whose Personal Information was Collected, an Empirical Analysis was Conducted to Compare the E-commerce Field and LBS(Location Based Service) Field. The Results of Empirical Analysis are as follows. First, it is Founded that other Relations were All Statistically Significant Except the Relation between Privacy Risk and Information Disclosure Behavior in the LBS group. Next, as a Results of Comparison of Constructs in the E-commerce and Institutional trust than the LBS group, Identifying that the Consumers are more Sensitive to the Personal Information Collected in the E-commerce site.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.868-870
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• 2013

전자의무기록(Electronic Medical Record, EMR) 시스템은 기존에 수기로 작성하던 의무기록을 디지털화 한 것이다. 이는 다양한 장점이 있지만 의료인이 관리 도메인을 통해 환자의 정보를 세밀하게 수집할 수 있는 환자 개인의 프라이버시 침해 문제가 발생하게 된다. 즉, 관계자에 의해 의도적인 유출이 발생하거나 의료정보의 거래, 복제 등 위험성이 존재한다. 특히 일부 의료정보는 고용 차별이나 사회적 차별 등 환자에게 정신적 고통을 안겨줄 수 있다. 이러한 프라이버시 침해는 유전성 질환 유전자를 가진 사람에게 유전적 요인에 근거하는 고용 차별이 발생할 수 있다. 관련연구에서는 환자의 임상적(Clinical) 또는 유전적(Genomic) 정보가 자신의 신원과 연계되어 있다면 프라이버시 침해가 발생할 수 있음을 나타낸다. 이러한 프라이버시 문제로 인해 EMR 시스템에 기반을 둔 전자건강기록(Electronic Health Record, EHR) 시스템 또한 개인 프라이버시 침해의 위험이 존재하게 된다. 따라서 의료정보의 프라이버시 보호를 위해 부당한 고용 차별 보험 차별 사회적 차별로 연결될 수 있는 개인 의료정보의 유출방지, 타인에게 알려지고 싶지 않은 개인 의료정보가 무단으로 거래되지 않는 것을 보장해야 한다. 이를 위해 본 논문에서는 의무기록의 익명화를 통해 환자와 의무기록 간의 관계를 제거하는 여러 방법들을 소개한다.

• Journal of Digital Convergence
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• v.15 no.12
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• pp.265-272
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• 2017

As Location-based services on smartphone are getting more popular, users have more concern on exposing their location information. This study developed a research model to identify how smartphone users perceive on providing information pertaining to their location based on privacy calculus theory. 203 responses were analyzed with SmartPLS 2.0. The outcome of this research is quite interesting because conventional belief of privacy calculus perspective does not hold. The privacy calculus theory is based on assumption that human being is rational and decision to provide privacy information is determined by risk and benefit aspects. However, the result of this study is in accordance with behavioral economics perspective in which emotional judgment and behavioral judgement are affected by different factors.

• 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.

• 정보보호뉴스
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• no.9 s.132
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• pp.22-24
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• 2008

개인정보보호에 대한 관심과 사회적 이슈는 국내뿐만이 아니라, 전 세계적인 공동의 관심사로 떠오른지 오래다. 국제기구가 프라이버시 보호 법안을 제정해 각국 정부에 권고하는 한편, 개인정보보호, 프라이버시 보호와 비즈니스의 연관관계를 분석하는 시도가 늘어나고 있다. 국제적인 컨설팅 그룹 딜로이트에서 보안 프라이버시와 데이터 보호 분야를 맡고 있는 Ken DeJarnette에게 비즈니스와 개인정보 및 프라이버시 보호의 연관성에 대해 다양한 조언을 요청했다.

• Journal of the Korea Society of Computer and Information
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• v.27 no.1
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• pp.193-200
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• 2022

In this paper, we examined the causes of privacy concerns and related factors in social log-in services. On the basis of the 'principal-agent theory,' we established factors such as perceived information asymmetry and fear of seller opportunism affecting information privacy concern of social log-in services users. In addition, we analyzed the relationship between the information privacy concern and intention to use on the basis of the 'privacy calculus theory'. The results of the study showed that (1) fear of seller opportunism had the significant effect on information privacy concerns, (2) information privacy concerns had the significant effect on perceived risk, (3) in accordance with the privacy calculus theory, perceived risk had the negative effect on intention to use, while perceived benefit had the positive effect on intention to use. The findings of the study are expected to help to improve the social log-in service firms' understanding for customers' information privacy protection behaviors.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.65-72
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• 2016

This study built the theoretical frameworks for empirical analysis based on the analysis of the relationship among the concepts of risk of information privacy, the experience of information privacy, the policy of information privacy and information control via the provision intention studies. Also, in order to analyze the relationship among the factors such as the risk of information privacy, intention to offer the personal information, this study investigated the concepts of information privacy and studies related with the privacy, established a research model about the information privacy. Followings are the results of this study: First, the information privacy risk, information privacy experience, information privacy policy, and information control have positive effects upon the information privacy concern. Second, the information privacy concern has the negative effects upon the provision intention of personal information.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.47-54
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• 2022

Recently, with the development of deep learning technology, research on recognizing human behavior is in progress. In this paper, a study was conducted to recognize risky behaviors that may occur in a single-person household environment using deep learning technology. Due to the nature of single-person households, personal privacy protection is necessary. In this paper, we recognize human dangerous behavior in privacy protection video with Gaussian blur filters for privacy protection of individuals. The dangerous behavior recognition method uses the YOLOv5 model to detect and preprocess human object from video, and then uses it as an input value for the behavior recognition model to recognize dangerous behavior. The experiments used ResNet3D, I3D, and SlowFast models, and the experimental results show that the SlowFast model achieved the highest accuracy of 95.7% in privacy-protected video. Through this, it is possible to recognize human dangerous behavior in a single-person household environment while protecting individual privacy.

• Information Systems Review
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• v.25 no.3
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• pp.99-120
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• 2023

Courier services users' experience of violating privacy affects psychology and behavior of protecting personal privacy. Depending on what privacy infringement experience (PIE) of courier services users, learning about perceived privacy infringement incidents is made, recognition is formed, affection is formed, and behavior is appeared. This paradigm of changing in privacy psychologies of courier services users has an important impact on predicting responses of privacy protective action (PPA). In this study, a theoretical research framework are developed to explain the privacy protective action (PPA) of courier services users by applying attitude theory. Based on this framework, the relationships among past privacy infringement experience (PIE), perceived privacy risk (PPR), privacy concerns (i.e., concerns in unlicensed secondary use (CIUSU), concerns in information error (CIE), concerns in improper access (CIA), and concern in information collection (CIC), and privacy protective action (PPA) are analyzed. In this study, the proposed research model was surveyed by people with experience in using courier services and was analyzed for finding relationships among research variables using structured an equation modeling software, SMART-PLS. The empirical results show the causal relationships among PIE, PPR, privacy concerns (CIUSU, CIE, CIA, and CIC), and PPA. The results of this study provide useful theoretical implications for privacy management research in courier services, and practical implications for the development of courier services business model.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.749-752
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• 2024

연합학습은 클라이언트가 중앙 서버에 원본 데이터를 주지 않고도 학습할 수 있도록 설계된 분산된 머신러닝 방법이다. 그러나 클라이언트와 중앙 서버 사이에 모델 업데이트 정보를 공유한다는 점에서 여전히 추론 공격(Inference Attack)과 오염 공격(Poisoning Attack)의 위험에 노출되어 있다. 이러한 공격을 방어하기 위해 연합학습에 차분프라이버시(Differential Privacy)를 적용하는 방안이 연구되고 있다. 차분 프라이버시는 데이터에 노이즈를 추가하여 민감한 정보를 보호하면서도 유의미한 통계적 정보 쿼리는 공유할 수 있도록 하는 기법으로, 노이즈를 추가하는 위치에 따라 전역적 차분프라이버시(Global Differential Privacy)와 국소적 차분 프라이버시(Local Differential Privacy)로 나뉜다. 이에 본 논문에서는 차분 프라이버시를 적용한 연합학습의 최신 연구 동향을 전역적 차분 프라이버시를 적용한 방향과 국소적 차분 프라이버시를 적용한 방향으로 나누어 검토한다. 또한 이를 세분화하여 차분 프라이버시를 발전시킨 방식인 적응형 차분 프라이버시(Adaptive Differential Privacy)와 개인화된 차분 프라이버시(Personalized Differential Privacy)를 응용하여 연합학습에 적용한 방식들에 대하여 특징과 장점 및 한계점을 분석하고 향후 연구방향을 제안한다.