• Journal of Platform Technology
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• v.10 no.1
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• pp.29-34
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• 2022

The emergence of new diseases such as the Covid 19 pandemic that occurs in the 21st century and the occurrence of health abnormalities according to the busy daily life of modern people are increasing. Accordingly, the importance of health care management and data-based health management is being highlighted, and in particular, interest in personal health management data based on personal health care data of patients is rapidly increasing. In this study, to solve the difficult problems of personal health management, we developed a personal health care platform incorporating IT for self-diagnosis and solution and developed an application that measures bio-signals generated in the human body and transmits them to the platform. A health management system was established. Through this, not only the health care of modern people, but also the psychological and emotional care support needs through psychological and emotional monitoring of the developmentally disabled and the vulnerable who have difficulty in expressing their opinions are to be addressed. In addition, the overall health and living environment data of the individual was integrated to develop an optimized medical and health management service for the individual.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.5
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• pp.117-123
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• 2016

In recent years, Personal Health Record (PHR) has emerged as a patient-centric model of health information exchange. The Personal Health Record (PHR) owners enjoy the full right of accessing their records anywhere and anytime making storage and retrieval more efficient. Due to the sensitivity and confidential nature of the PHR, however, the PHR is maintained in a secure and private environment with the individual determining rights of access. In this paper, we propose a system which enables access to the user's PHR in the event of emergency. In emergency situation where the user is unconscious, the emergency staff can use the PHR information to request a emergency access to the PHR server based on the predefined rights of access for PHR. Under the proposed system, the PHR owner can specify a fine grain access control policy during emergency situations.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.4
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• pp.197-202
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• 2017

The remote healthcare monitoring system enables a doctor to diagnose and monitor patient's health problem from a distance. Previous researches have focused on key establishment method between a patient and a particular doctor to solve personal health information disclosure problem in data transmission process. However, when considering a misdiagnosis of doctor, the result of a diagnosis by a many doctors is more reliable. In previous work, in order to select multiple doctors, patient should generate shared key for each chosen doctor and perform many times encryptions. Therefore, in this paper, we propose a secure data transmission protocol for receiving diagnosis from multiple doctors using identity-based proxy re-encryption scheme. In proposed protocol, a patient don't need key management work for session key. Also, monitoring server performs re-encryption process on behalf of patient. So, we can reduce computational burden of patient in previous work.

• Journal of Convergence for Information Technology
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• v.9 no.9
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• pp.27-32
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• 2019

Along with the growth of u-Healthcare, we propose a security enhancement based on network separation for CloudHIS with for handling healthcare information to cope with cyber attack. To protect against all security threats and to establish clear data security policies, we apply desktop computing servers to cloud computing services for CloudHIS. Use two PCs with a hypervisor architecture to apply physical network isolation and select the network using KVM switched controller. The other is a logical network separation using one PC with two OSs, but the network is divided through virtualization. Physical network separation is the physical connection of a PC to each network to block the access path from both the Internet and the business network. The proposed system is an independent desktop used to access an intranet or the Internet through server virtualization technology on a user's physical desktop computer. We can implement an adaptive solution to prevent hacking by configuring the CloudHIS, a cloud system that handles medical hospital information, through network separation for handling security enhancement.

• Smart Media Journal
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• v.5 no.1
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• pp.114-121
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• 2016

Currently, different medical institutions have been carrying out the e-healthcare system project. The system includes electronic medical record and prescription delivery system, and, the Medical Treatment law permits electronic signature for medical record management, which reduced the relevant costs and enabled sharing medical record. And medical solution using online certificates is expanding its application. In that light, the role of certificates became more important than ever. However, in contrast to active effort made to manage personal certificates, certificates related to medical solutions and other types of work are not being managed properly. Most work-related certificates are saved in office computers, which makes them vulnerable to various security threats. Although certificate servers can be used as a solution to this problem, hospitals must build the server separately and, therefore, small and medium-size hospitals can be reluctant to bear the burden. This study proposed a way to design and implement an effective and secure certificate management system by save the certificate file as a BLOB, using existing resources without needing to build a separate certificate server, at minimized costs.

• The Transactions of the Korea Information Processing Society
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• v.13 no.2
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• pp.76-90
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• 2024

Although artificial intelligence (AI) can be utilized in various domains such as smart city, healthcare, it is limited due to concerns about the exposure of personal and sensitive information. In response, the concept of distributed machine learning has emerged, wherein learning occurs locally before training a global model, mitigating the concentration of data on a central server. However, overall learning phase in a collaborative way among multiple participants poses threats to data privacy. In this paper, we systematically analyzes recent trends in privacy protection within the realm of distributed machine learning, considering factors such as the presence of a central server, distribution environment of the training datasets, and performance variations among participants. In particular, we focus on key distributed machine learning techniques, including horizontal federated learning, vertical federated learning, and swarm learning. We examine privacy protection mechanisms within these techniques and explores potential directions for future research.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.97-110
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• 2022

Federated learning is a learning method capable of performing model learning without transmitting learning data. The IoT or healthcare field is sensitive to information leakage as it deals with users' personal information, so a lot of attention should be paid to system design, but when using federated-learning, data does not move from devices where data is collected. Accordingly, many federated-learning implementations have been developed, but detailed research on system design for the development and operation of systems using federated learning is insufficient. This study shows that measures for the life cycle, code version management, model serving, and device monitoring of federated learning are needed to be applied to actual projects and distributed to IoT devices, and we propose a design for a development environment that complements these points. The system proposed in this paper considered uninterrupted model-serving and includes source code and model version management, device state monitoring, and server-client learning schedule management.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.506-509
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• 2017

Opinion mining is a way to analyze the emotions in the text and is used to identify the emotional state of the author and to find out the opinions of the public. As you can analyze individual emotions through opinion mining, if you analyze the text by region, you can find out the emotional state you have in each region. The regional sentiment analysis can obtain information that could not be obtained from personal sentiment analysis, and if a certain area has emotions, it can understand the cause. For regional sentiment analysis, we need text data created by region, so we need to collect data through Twitter crawling. Therefore, this paper designs a Twitter data collection system for regional sentiment analysis. The client requests the tweet data of the specific region and time, and the server collects and transmits the requested tweet data from the client. Through the latitude and longitude values of the region, it collects the tweet data of the area, and it can manage the text by region and time through collected data. We expect efficient data collection and management for emotional analysis through the design of this system.