• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.153-154
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• 2023

본 연구에서는 인간의 의사소통이 갖고 있는 복잡한 과정을 고려하여 재난 시 위험의 소통방식에서 나타나는 오류들을 분석하고, 안전문화를 정착시키기 위한 방법 중 가장 효과적인 방법의 하나로 "위험소통"을 그 대안으로 제시하고자 하였다. 또한 안전문화를 개인의 과제가 아닌 조직 내에서의 협동과제로 인식하고, 조직 내 소통을 통한 신뢰가 안전문화에 미치는 영향력에 집중하였다. 본 연구의 제안을 통해 위험소통에 대한 새로운 원칙들을 제시함으로써 조직 내 안전문화의 새로운 방향을 도모하고자 한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.51-62
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• 2022

This study suggests a design of predictive modeling for a hospital fall risk based on inpatients' posture. Inpatient's profile, medical history, and body measurement data along with basic information about a bed they use, were used to predict a fall risk and suggest an algorithm to determine the level of risk. Fall risk prediction is largely divided into two parts: a real-time fall risk evaluation and a qualitative fall risk exposure assessment, which is mostly based on the inpatient's profile. The former is carried out by recognizing an inpatient's posture in bed and extracting rule-based information to measure fall risk while the latter is conducted by medical staff who examines an inpatient's health status related to hospital fall risk and assesses the level of risk exposure. The inpatient fall risk is determined using a sigmoid function with recognized inpatient posture information, body measurement data and qualitative risk assessment results combined. The procedure and prediction model suggested in this study is expected to significantly contribute to tailored services for inpatients and help ensure hospital fall prevention and inpatient safety.

• Information Systems Review
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• v.25 no.1
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• pp.165-187
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• 2023

The continuous increase in life expectancy and high interest in health has brought about significant changes in the use of health information by the public according to the development of information technology represented by the Internet and smartphones. As the medical market expands to the mobile health environment, many health-related apps have been created and distributed, but the acceptance rate is slow as it has become challenging to provide services due to various regulations. In this study, perceived value, perceived risk factors (psychological risk, risk of time-loss, legal risk), and perceived benefits (usefulness, interaction, autonomy) were derived and verified as factors that affect the acceptance resistance of personal health record apps based on the privacy calculation model. In addition, by analyzing the moderating effect of trust in the manufacturer, how the perceived risk and perceived benefit affect the perceived value was verified. A survey was conducted on Korean college students who recognized the personal health record apps but did not use them, and 127 samples were analyzed using structural equations. As a result of hypothesis verification, perceived value has a negative effect on acceptance resistance, perceived risk (risk of time-loss) has a negative effect on perceived value, and perceived benefits (usefulness, interaction, autonomy) were found to have a positive effect on perceived value. Trust in manufacturers has weakened the impact of perceived risks (legal risk) on perceived values. This study is expected to play an important role in maintaining a competitive advantage in the personal health record app market environment by identifying and proposing detailed criteria for reducing the acceptance resistance of personal health record apps.

• Korean Journal of Culture and Social Issue
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• v.13 no.3
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• pp.89-109
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• 2007

This study is an exploratory study on stock investment behaviors of individual investors in psychological perspective. The study is based on many behavioral finance studies which overconfidence of individual investors has an effect on irrational investment decision making and investment behaviors such as excessive trading. Accordingly, this study was to investigate the factors of self-enhancement perception on confidence of investment of individual investors and to find whether these psychological biases lead to irrational investment behaviors. The results indicated that there were sex differences in the factors of self-enhancement perception on individual investors' confidence of investment. In case of male investors, they were confident of their ability of investment but in case of female investors, they were confident of optimistic expectation of return. Also, male investors were more confident of investment than female investors. In addition, the result showed that risky investment behaviors of individual investors were influenced by psychological factors such as favorable self-evaluation, confidence of self-controllability, optimistic expectation of return and confidence of investment in part. This study suggests that further researches need to search after other variables which can mediate between psychological factors and investment behaviors of individual investors.

• Review of KIISC
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• v.24 no.6
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• pp.25-30
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• 2014

최고 수준의 IT인프라를 활용하는 클라우드 컴퓨팅 서비스의 확산에 따라 스마트 폰을 활용하여 언제든지 원하는 서비스 요청이 가능하게 되었다. 그러나 이러한 최신 IT서비스의 이면에는 보안 위협이 존재한다. 클라우드 서비스를 통해 데이터 뿐 아니라 개인정보의 수집 및 활용 또한 용이해지면서, 개인정보 유 노출 및 악용의 위험이 높아지고 있어, 이러한 사항을 고려한 클라우드 보안 방안을 마련할 필요가 생겼다. 클라우드 컴퓨팅 서비스 제공자가 개인정보보호에 대한 충분한 방안을 마련하고 시행할 수 있도록, 정부의 법제 마련 등 범국가적 지원이 필요한 상황이다. 이에 정부는 2013년부터 추진하고 있는 "클라우드 컴퓨팅 발전 및 이용자 보호에 관한 법률안"을 통해 클라우드 산업 활성화를 위하여 정부가 지원 방안을 마련하고자 하나, 개인정보에 대한 세밀한 검토 후 수정 보완 하여 한다는 의견이 있어, 현재 국회에 계류중이다. 본고에서는 클라우드 컴퓨팅 서비스의 발전과 클라우드 환경에서의 개인정보보호 이슈를 정리 해보고, 클라우드 컴퓨팅 서비스를 이용하는 서비스 이용자의 개인정보 안전성을 보장하고 서비스 제공자의 잠재적 개인정보 침해 위험을 줄일 수 있는 방향을 생각 해 보고자 한다.

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

• Information Systems Review
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• v.18 no.3
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• pp.185-207
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• 2016

This study investigated the relationship between privacy policy awareness and willingness to provide personal information. Online privacy policies published on the Internet aim to build the trust of consumers and reduce their concerns about the provision of providing personal information. This study uses FIP(FIP; Fair Information Practices) principles to measure awareness of privacy policy. The result of the survey indicates significant relationships among awareness of privacy policy of e-commerce websites, privacy trust, and privacy risk. Privacy policy aims to improve transparency of collection and use of personal information. A high level of privacy trust is related to a high level of willingness to provide personal information on an e-commerce website. A low level of privacy risk is related to a high level of willingness to provide personal information on an e-commerce website. This study found that disposition to trust moderates the relationship between privacy policy awareness and privacy trust. This study contributes to further research on the relationships among privacy policy awareness, privacy trust, and privacy risk. The result of this study can be used by companies that aim to build privacy trust and reduce privacy risk.

• Korean Journal of Social Welfare Studies
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• v.48 no.1
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• pp.143-171
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• 2017

This study aims to examine experiences of homeless risk factor before becoming the homeless focusing during their childhood period. This study underscore their victimization experience in their previous life with life history interviews of 60 homeless adults. As a result, this study identified various individual homeless risk factors they experienced for a long time. Also the risk factors were interactive, amplified and affect becoming homeless in the end. Moreover the results proved different characteristics between the group according how often they experienced homeless risk factors. These results show that the individual factors emerging homeless also start early stages of their life and those were invincible misfortune and victimization. These findings suggest that the government policy and proactive intervention in order to prevent homeless in the early stage need to be established and have more concerns about high risk youth.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.2
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• pp.395-410
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• 2015

This research defines the degree of the threat caused by the leakage of personal information in a quantitative way. The proposed definition classifies the individual items in a personal data, then assigns a risk value to each item. The proposed method considers the increase of the risk by the composition of the multiple items. We also deals with various attack scenarios, where the attackers seek different types of personal information. The concept of entropy applies to associate the degree of the personal information exposed with the total risk value. In our experiment, we measured the risk value of the Facebook users with their public profiles. The result of the experiment demonstrates that they are most vulnerable against stalker attacks among four possible attacks with the 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.