• Review of KIISC
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• v.19 no.3
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• pp.35-45
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• 2009

개인신원검증은 사용자가 자원 및 시스템에 접근할 수 있는 자격을 증명하고, 사용자가 요청한 업무를 수행하기 위해 필요한 권한을 부여 받는 과정이다. 즉 인증 과정이 성공적으로 수행된 후 인가 수준을 결정하는 중요 요소로서 활용된다. 이러한 개인신원검증은 신원 도용, 변조의 위험과 비인가 된 사용자의 접근을 허용할 수 있는 문제점을 가지고 있다. 이에 따라 국 내외적으로 개인신원검증에 대한 다양한 연구가 진행되고 있다. 따라서 본 고에서는 NIST의 FIPS 201-1에서 규정하는 개인신원검증에 대한 주요 인프라, 인증 메커니즘, 암호키에 대한 기술적인 세부 내용을 분석하고자 한다.

• 월간 기계설비
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• no.9 s.206
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• pp.24-25
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• 2007

인터넷 사용인구가 급속도로 증가하면서 피해발생이 위험수위를 넘어섬에 따라 정보통신부가 정보통신망에서의 개인정보 수집.이용.제공에 대한 고지 및 동의제도 개선.보완, 개인정보 취급 위탁 관리.감독 강화, 개인정보취급방침 공개 의무화 등 개인정보 보호강화를 확대하고 지난 7월 27일부터 시행에 들어갔다. 정보통신부에 따르면 정보통신망에서의 이용자 보호 및 개인정보 보호 강화를 내용으로 하는 개정"정보통신망 이용촉진 및 정보보호 등에 관한 법률"(이하 정보통신망법) 및 동법 시행령과 시행규칙이 개정되어 지난 7월 27일부터 동시에 시행됐다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.1
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• pp.207-214
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• 2014

Recently, smartphone spyware resembles various types of virus components in PCs and has trends getting more and more severe. Users do not perceive the risk factors severely even if smartphone security is very vulnerable in spite of the smartphone spyware growth. Thus, this study observes the influence of information security in selecting smartphone based on the personal inclinations and spyware perceptions. The main variables of study model are such as the degree of personal risk-accepting and the risk of smartphone spyware as independent variables and smartphone purchasing intention as a dependent variable. The model is tested using SPSS 21 packages on the effective 200 samples gathered through questionnaire survey on the present smartphone users. As a result, the two main hypotheses which are "the degree of personal risk-accepting will influence on the perceiving risk of smartphone spyware" and "the perceiving risk of smartphone spyware will influence on smartphone purchasing intention" were significant statistically. Therefore, we could find out information security's influence on the selecting smartphone.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.719-734
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• 2020

This paper proposes a new measurement scheme for estimating the processing level according to risk when performing de-identification in the use of personal information by practitioners in the organization in line with the recently revised Data 3 Act. Our proposed methods considered the surrounding circumstances surrounding the data, not just the data, for risk measurement, and divided the data situation into three categories more systematically so that it can be applied in all areas in a general-purpose environment, the data utilization environment, and the data (self) so that it can be calculated quantitatively based on each context risk according to the presented classification. The proposed method is designed to calculate the risk of existing de-identifiable information in a quantitative manner so that personal information controller in general organizations can use it in practice, not just in the qualitative judgment of experts.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.6
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• pp.73-82
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• 2012

This paper reviews Privacy Impact Assessments in order to perform preventing and diagnosis against potential threats focused on the C-Shopping mall case. The quality of protection in C-shopping mall shows that the corporations itself is 29.2, the system is 68.8, the life cycle of the privacy is 25.5 and CCTV is 60.0. The lowest levels are the corporation's management 16.7, the life-cycle's saving and keeping 12.5, usage and offer 11.5 and destruction 16.7 among the life cycle of the privacy. The result of risk analysis shows that the highest levels are saving and keeping 13.3 and destruction 13.0. From the result, dangerous duplications are saving and keeping and destructions.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.561-564
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• 2016

If using crime map which represents criminal section that violent crimes targeting women frequently happened, the police could prevent additional crimes by positioning themselves intensively in expected crime zones and each individual could avoid being damaged by referring information of criminal zones. In this paper, by analyzing crimes targeting women and offender information which is provided in public-opened datum portal, we suppose a system which prevents crimes that calculates locational danger and, by considering location and age group of users, provides user-customized information of danger. By crawling the criminals datum which is provided in public-opened datum portal, It collects them. About the areas which happened sexual crimes, calculating danger of crime based on statistical crime information including criminal information, residence of offenders, areas which happened sexual crimes, sentences and the number of crime, this system is able to visualize the areas which sexual crimes happened based on information of danger grade representing on user's location. The score of danger calculated in location unit can provide criminal information according to location and ages of users by interacting GIS.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5771-5777
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• 2013

The need of continuous management for diseases came to the fore as a chronic disease has increased, however, research related to personalized food intake analysis are insufficient. In diabetes risk analysis model of this study, food preferences are calculated by Pearson correlation coefficient that is proven method to assess the similarity, and diabetes risk is computed as a Logistic regression that was used in prevalence studies. For the Significance evaluation of this model, it was verified through t-test at 0.05 level of 52 comparison subjects and 52 control subjects. Both groups were significantly independent (p=0.046 <0.05). This model is a new way to personalized health management, through the application to healthcare system based on web and mobile.

• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.65-77
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• 2021

COVID-19 has recently impacted the world with the large numbers of infected and deaths. The development of effective COVID-19 vaccine has not been successful. Hence, people have a high concern on the infection of this disease. The infection information from the governmantal public organizations are mainly based on simple summary statistics. Consequently, it is hard to assess the infection risks of individual person and the current location of the person. In this paper, we present a machine learning-based software system that analyzes COVID-19 infection risks and guidelines for safe activities.This paper proposes a suite of risk factors regarding COVID-19 infection and deaths and methods to quantitatively measure the individual and group risks using the proposed metrics. The proposed system utilizes a clustering algorithms and various software approaches that reflect the information and features of inviduals and their geograpical locations.

• Journal of the Korea Society of Computer and Information
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• v.29 no.7
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• pp.53-71
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• 2024

Generative Artificial Intelligence (AI) has become the focus of societal attention due to its wide range of applications and profound impact. This paper constructs a comprehensive theoretical model based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), integrating variables such as Personal Innovativeness and Perceived Risk to study the key factors influencing enterprises' adoption of Generative AI. We employed Structural Equation Modeling (SEM) to verify the hypothesized paths and used the Bootstrapping method to test the mediating effect of Behavioral Intention. Additionally, we explored the moderating effect of Perceived Risk through Hierarchical Regression Analysis. The results indicate that Performance Expectancy, Effort Expectancy, Social Influence, Price Value, and Personal Innovativeness have significant positive impacts on Behavioral Intention. Behavioral Intention plays a significant mediating role between these factors and Use Behavior, while Perceived Risk negatively moderates the relationship between Behavioral Intention and Use Behavior. This study provides theoretical and empirical support for how enterprises can effectively adopt Generative AI, offering important practical implications.