• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.251-258
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• 2012

The protection of medical information by major Issues on medical information to protect the individuals' privacy on medical information. Especially, Issues of medical service information, medical record, insurance, employment, Genetic technology including genetic test and screening, gene therapy and genetic enhancement is developing rapidly. Defensibility of medical information documentation is tested in the courts. medical information can be illicitly accessed from anywhere and transmitted across the quickly and with risk of detection. Once data is distributed on the internet, it may become available to anyone who wishes to purchase it, and it cannot be expunge. Patient privacy protection of medical information is controlled mostly by patient consent laws that define how and when a patient must consent before a physician may disclose the patient's medical information to anyone else. enterprise that offers consumers commodities or services is checking problem about customer information of management system is checking problem about customer information of management system essentially. Therefore, in this paper will find a way out to Protection of medical information by major Issues on medical information.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.505-514
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• 2012

Because people usually establish their online social network based on their offline relationship, the social networks (i.e., the graph of friendship relationships) are often used to share contents. Mobile devices let it easier in these days, but it also increases the privacy risk such as access control of shared data and relationship exposure to untrusted server. To control the access on encrypted data and protect relationship from the server, M. Atallah et al. proposed a hop-based scheme in 2009. Their scheme assumed a distributed environment such as p2p, and each user in it shares encrypted data on their social network. On the other hand, it is very inefficient to keep their relationship private, so we propose an improved scheme. In this paper, among encrypted contents and relationships, some authenticated users can only access the data in distributed way. For this, we adopt 'circular-secure symmetric encryption' first. Proposed scheme guarantees the improved security and efficiency compared to the previous work.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.742-756
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• 2022

A flood of information has occurred with the rise of the internet and digital devices in the fourth industrial revolution era. Every millisecond, massive amounts of structured and unstructured data are generated; smartphones, wearable devices, sensors, and self-driving cars are just a few examples of devices that currently generate massive amounts of data in our daily. Machine learning has been considered an approach to support and recognize patterns in data in many areas to provide a convenient way to other sectors, including the healthcare sector, government sector, banks, military sector, and more. However, the conventional machine learning model requires the data owner to upload their information to train the model in one central location to perform the model training. This classical model has caused data owners to worry about the risks of transferring private information because traditional machine learning is required to push their data to the cloud to process the model training. Furthermore, the training of machine learning and deep learning models requires massive computing resources. Thus, many researchers have jumped to a new model known as "Federated Learning". Federated learning is emerging to train Artificial Intelligence models over distributed clients, and it provides secure privacy information to the data owner. Hence, this paper implements Federated Averaging with a Deep Neural Network to classify the handwriting image and protect the sensitive data. Moreover, we compare the centralized machine learning model with federated averaging. The result shows the centralized machine learning model outperforms federated learning in terms of accuracy, but this classical model produces another risk, like privacy concern, due to the data being stored in the data center. The MNIST dataset was used in this experiment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.639-641
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• 2022

With the increasing of aging population, a lot of researches on monitoring systems for solitary senior citizens are under study. In general, a monitoring system provides a monitoring service by computing the information of vision, sensors, and measurement values on a server. Design considering data security is essential because a risk of data leakage exists in the structure of the system employing the server. In this paper, we propose a intelligent monitoring system for solitary senior citizens with vision-based security architecture. The proposed system protects privacy by ensuring high security through an architecture that blocks communication between a camera module and a server by employing an edge AI module. The edge AI module was designed with Verilog HDL and verified by implementing on a Field Programmable Gate Array (FPGA). We tested our proposed system on 5,144 frame data and demonstrated that a dangerous detection signal is generated correctly when human motion is not detected for a certain period.

• Convergence Security Journal
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• v.24 no.2
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• pp.133-140
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• 2024

The spread of Direct-to-Consumer (DTC) genetic testing, where users request tests directly, has been increasing. With growing demand, certification systems have been implemented to grant testing qualifications to non-medical institutions, and the scope of tests has been expanded. However, unlike cases in less regulated foreign countries, disease-related tests are still excluded from the domestic regulations. The existing de-identification method does not adequately ensure the uniqueness and familial sharing of genomic information, limiting its practical utility. Therefore, this study proposes the application of fully homomorphic encryption in the analysis process to guarantee the usefulness of genomic information while minimizing the risk of leakage. Additionally, to safeguard the individual's right to self-determination, a privacy preservation model based on Opt-out is suggested. This aims to balance genomic information protection with maintainability of usability, ensuring the availability of information in line with the user's preferences.

• The Korean Journal of Applied Statistics
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• v.21 no.2
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• pp.313-325
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• 2008

Large amounts of information on individuals is available to many organizations and data users and government agencies release microdata files from their survey data or administrative records data. However, if a microdata file is released without any limitation, an invasion of privacy is likely to occur. Therefore, in creating a microdata file, agencies attempt to eliminate disclosure risk of the file while maintaining maximum utility of the data. In this paper, we introduce the concept of disclosure risk, identification and uniqueness. Also, we show the method for creating a 2% microdata file using the 2005 Korean census microdata.

• Journal of Information Technology Applications and Management
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• v.26 no.6
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• pp.29-46
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• 2019

This study analyzed the factors influencing the technology acceptance of the general public in the drones and ARs, one of the key technologies of the industry 4.0. The theoretical basis was the extended unified theory of acceptance and use of technology model(UTAUT2), which uses performance expectancy, effort expectancy, social influence, facilitating conditions, and hedonic motivation as factors common to both services. The price value factor was excluded considering that most ARs were free, and the perceived risk factors, including privacy, which were not in UTAUT2, were included because they are important factors for ICT technology acceptance. The hypothesis was tested by structure equation model. Social influence and hedonic motivation had a positive(+) effect on intention to use technology. On the other hand, in the case of effort expectancy, neither the AR nor the drone had a significant influence on intention to use technology. Furthermore, performance expectancy had a positive(+) effect on intention to use in AR, but no significant influence was found out in drones. On the contrary, in the case of the facilitating conditions, the influence of the drones was positive (+), but the relation of AR was not investigated. The perceived risk was tested for the negative (-) influence of use intention of AR, but no significant relationship was found out for the drones. Among the significant influencing factors, hedonic motivation was the most powerful factor in AR and drones. Theoretical and practical implications are presented based on these results.

• Journal of Digital Contents Society
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• v.15 no.1
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• pp.121-128
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• 2014

SSE-CMM for security engineering, engineering, assurance, risk is divided into three elements of the process maturity assessment model and the level of information security presented. Maturity measurement of privacy, vulnerability diagnosis and risk analysis methodologies is used in practical field for present a comprehensive conclusion. The common cyber services are internet banking, mobile banking, telephone banking and the like. Transaction structure, a kind of cyber-banking system, information security maturity of the existing measurement methodologies for research purposes, vulnerability diagnosis and risk analysis methodologies to be used in practical field present a comprehensive conclusion. To ensure safety and convenience for the user, convenient to deal with cyber environment is the key to the activation of cyber trading. Particularly by measuring the maturity of cyber banking system to ensure the safety of the practice field much effects are expected as a result.

• Journal of the Korea Society of Computer and Information
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• v.29 no.10
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• pp.77-87
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• 2024

With the recent advancements in artificial intelligence, various chatbots have emerged, efficiently performing everyday tasks such as hotel bookings, news updates, and legal consultations. Particularly, generative chatbots like ChatGPT are expanding their applicability by generating original content in fields such as education, research, and the arts. However, the training of these AI chatbots requires large volumes of conversational text data, such as customer service records, which has led to privacy infringement cases domestically and internationally due to the use of unrefined data. This study proposes a methodology to quantitatively assess the re-identification risk of personal information contained in conversational text data used for training AI chatbots. To validate the proposed methodology, we conducted a case study using synthetic conversational data and carried out a survey with 220 external experts, confirming the significance of the proposed approach.

• Management & Information Systems Review
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• v.28 no.4
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• pp.45-66
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• 2009

This research investigates the systematic relation between corporate governance and corporate social responsibility(CSR). Based on the argument that corporate governance would play the role of mitigating conflicts between firms and society, we hypothesized that corporate governance would enhance CSR performance. Specifically, the firms with good governance are predicted to have CSR performance than those with bad governance. These hypotheses were tested using 130ce rean firms from 1998 to 2005. An index published by e rean Economic Justice mance the(KEJm) was used as the measureses wSR performance. Our empirical results suggest that the firms with good governance as measured by f reign investh bad goothshae directh bad goirdit committee exhibit better CSR performance. The primary purposeses this s tdy is to identify the determinants es the use b' satissaction and commitment in pe bn thomedia. For these purposes, we developegoi research modehobased on the literaturesreviews es pe bn tho media, pe ceived risk and interactivity, satissaction, and commitment. This study has identified four dimensions in the concept of perceived risk, such as privacy risk, social risk, time loss risk, and economic risk, and three dimensions in the concept of perceived interactivity, such as active control, two-way communication, and responsiveness.