• Knowledge Management Research
• /
• v.22 no.2
• /
• pp.33-53
• /
• 2021

Use of mobile apps being extended, privacy concern on the side of the users is increased while they are willing to provide the private information to use the apps. In this study, we tried to identify the motivating elements that influence the users' intention to use the apps, based on the tendency towards regulatory focus and the privacy calculus theory. To verify the study model, we collected data from 151 adults who use health apps throughout the country, and analyzed the data using the PLS-SEM method. According to the result of the study, it was turned out that tendency towards promotion focus had negative impact on privacy concern and privacy danger, and tendency towards prevention focus had positive impact on privacy concern. Privacy concern had negative impact on the intention to use the mobile apps, and privacy benefit and privacy knowledge had positive impact on the intention to use the mobile apps. Finally, the intention to use the mobile apps had positive impact on the intention to continue to use the mobile apps. In this study, we identified different impacts of two types of tendency towards regulatory focus on privacy concern, and identified different influences on the intention to use the mobile apps accordingly.

• Information Systems Review
• /
• v.22 no.2
• /
• pp.101-120
• /
• 2020

This study investigates the effects of privacy psychological characteristics of B2C logistics services users on their willingness to comply with their logistics companies' information protection policy. Using cognitive valence theory as a theoretical framework, this study proposes a research model to examine the relationships between users' logistics security knowledge, privacy trust, privacy risk, privacy concern, and their willingness of information protection policy compliance. To test the proposed model, we conducted a survey from actual users of logistics services and collected valid 151 samples. We analyzed the data using a structural equation modeling software. The empirical results show that logistics security knowledge positively affects privacy trust; privacy concern positively influences privacy risk; privacy trust, privacy risk, and privacy concern positively influence behavioral willingness of compliance. However, logistics security knowledge does not affect behavioral willingness of compliance. The results of the study provide several contributions to the literature of B2C logistics services domain and managerial implications to logistics services companies.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.9
• /
• pp.81-92
• /
• 2023

A privacy model is a technique that quantitatively restricts the possibility and degree of privacy breaches through privacy attacks. Representative models include k-anonymity, l-diversity, t-closeness, and differential privacy. While many privacy models have been studied, research on selecting the most suitable model for a given dataset has been relatively limited. In this study, we develop a system for recommending the suitable privacy model to prevent privacy breaches. To achieve this, we analyze the data features that need to be considered when selecting a model, such as data type, distribution, frequency, and range. Based on privacy model background knowledge that includes information about the relationships between data features and models, we recommend the most appropriate model. Finally, we validate the feasibility and usefulness by implementing a recommendation prototype system.

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

• Proceedings of the Korea Contents Association Conference
• /
• 2018.05a
• /
• pp.23-24
• /
• 2018

최근 공격자의 사전 지식에 상관없이 개인 정보를 보호할 수 있는 차분 프라이버시 보호 기법에 대한 연구들이 진행되고 있다. 본 논문에서는 차분 프라이버시를 만족시키는 적은 수의 버킷을 가지는 히스토그램 공개 알고리즘을 소개하고 기존 알고리즘이 사용한 휴리스틱 방법의 문제와 개선 방법을 소개한다. 또한, 실험을 통해 개선한 방법이 기존의 알고리즘에 비하여 더 좋은 영역 합 질의 성능을 가지는 것을 보인다.

• Review of KIISC
• /
• v.16 no.4
• /
• pp.77-86
• /
• 2006

향후의 유비쿼터스 사회(U-Society)는 정보화에 따른 여러가지 새로운 위험들이 나타나는 사회가 될 것이며, 개인정보 생성, 수집 등을 통해 개인정보 지식베이스 형성을 가능하게 하는 정보위험사회의 도래가 예상되고 있다. 따라서, 사용자의 상황에 맞게 적응적(Adaptive)이고 적시적(Just-In-Time)으로 개인정보보호 서비스 제공이 가능한 새로운 프레임워크 개발이 요구된다. 본 논문에서는 U-Society와 프라이버시 개념의 변화 과정을 검토하고, 개인정보 및 프라이버시 침해의 유형을 비교 분석한다. 아울러, 기존 프라이버시 보호 프레임워크 모델인 WASP 아키텍쳐와 IBM의 TPM 작동 과정과 주요 기능을 살펴보고 이에 따른 문제점을 지적한다. 또한, 개인정보보호 대책을 수립하기 위해 개인정보의 라이프사이클 관점에서 수집, 저장/관리, 이용/제공, 폐기의 4단계로 분석하고 개인정보 라이프사이클에 따른 프라이버시 보호 프레임워크 모델을 제시한다.

• Knowledge Management Research
• /
• v.24 no.1
• /
• pp.51-72
• /
• 2023

Digital literacy is vital knowledge and ability of an individual in the information society. As the level of digital literacy increases, the interest in privacy protection increases. This change may hinder the use of digital technologies and services. This research examines (1) the mediating effect of online social participation and information veracity on smart device literacy and privacy concerns, and (2) the moderating effect of privacy literacy. Using Korean media panel survey data reported in 2020 and in 2021, this study analyzes the responses of 7,737 people who use smart devices and participate in online activities. SPSS and PROCESS Macro are used to test the research model and hypotheses. In the analysis of 2020 and 2021 survey, this research shows that smart device literacy has major effects on privacy concerns; confirms that the mediating effect of online social participation; moderated meditating effect of privacy literacy. Although information veracity is not significant in 2020, mediating and moderated mediating effects are found in 2021.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2011.11a
• /
• pp.751-754
• /
• 2011

최근 개인이 작성한 글과 사진, 동영상 등의 자료를 시간과 장소에 따라 저장 할 수 있는 라이프 로그 서비스들이 증가하고 있다. 이러한 정보들은 개인의 일상생활을 기록하는 것으로 민감한 프라이버시임에도 불구하고 관리에 취약하다. 스마트폰 환경에서 데이터를 저장하기 위해 SQLite를 이용하고, 이를 암호화하기 위한 방안으로 SEE와 SQLCipher가 있지만 전체 데이터를 암호화하는 방식으로 중요하지 않은 데이터까지 암호화하여 저장한다. 본 논문은 개인 정보 보호를 위한 방안으로 SQLite에서 SEED 암호를 이용하여 주요한 개인 정보를 컬럼 단위로 암호화한다. 즉 라이프로그 데이터를 개인 프라이버시 중요도에 따라 분류하고, 분류된 데이터 중에서 중요한 데이터만 선택적으로 암복호화 함으로써 기존 데이터 암호화 방식에 비해 암복호화에 소모되는 연산 시간을 감소시키고 라이프로그 데이터의 개인 정보 보안을 강화시키고자 한다.

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

• Knowledge Management Research
• /
• v.25 no.2
• /
• pp.49-68
• /
• 2024

Increasing concerns regarding personal data privacy have complicated the acquisition of customer data through online marketing. This study investigates factors influencing customers' willingness to disclose information via a generative AI-based chatbot. Drawing on privacy calculus theory and regulatory focus theory, we explore how customer regulatory focus and familiarity with the generative AI-based chatbot shape disclosure intentions. Our study, involving 473 participants, reveals that low familiarity with the chatbot leads individuals with a prevention focus to perceive higher privacy risks and lower perceived usefulness compared to those with a promotion focus. However, with high familiarity, these differences diminish. Moreover, individuals with a promotion focus show a greater inclination to disclose information when familiarity with the generative AI-based chatbot is low, whereas this regulatory focus does not significantly impact disclosure intentions when familiarity is high. Perceived privacy risks mediate these relationships, underscoring the importance of understanding familiarity with the generative AI-based chatbot in facilitating personal information disclosure.