• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제14권1호
• /
• pp.437-454
• /
• 2020

According to the privacy regulations of the health insurance portability and accountability act (HIPAA), patients' control over electronic health data is one of the major concern issues. Currently, remote access authorization is considered as the best solution to guarantee the patients' control over their health data. In this paper, a new biometric-based key management scheme is proposed to facilitate remote access authorization anytime and anywhere. First, patients and doctors can use their biometric information to verify the authenticity of communication partners through real-time video communication technology. Second, a safety channel is provided in delivering their access authorization and secret data between patient and doctor. In the designed scheme, the user's public key is authenticated by the corresponding biometric information without the help of public key infrastructure (PKI). Therefore, our proposed scheme does not have the costs of certificate storage, certificate delivery, and certificate revocation. In addition, the implementation time of our proposed system can be significantly reduced.

• 예술인문사회 융합 멀티미디어 논문지
• /
• 제6권8호
• /
• pp.15-23
• /
• 2016

최근 국내와 국외에서 의료정보의 2차 활용에 대한 관심이 대두되고 있다. 그러나 국내의 법안이나 지침 등을 보았을 때 의료정보에 특화되어있다고 말할 수 있는 것은 지난 2012년 보건복지부와 행정안전부에서 발표된 '국내 의료기관 개인정보보호 가이드라인'정도로 볼 수 있다. 그러나 이 가이드라인도 의료정보에서 개인정보보호관련 법률에 저촉되는 것만을 제시하고, 의료정보 2차 활용을 위해 제거해야할 비식별화 대상 정보를 명확히 정의하고 있지 않다. 따라서 본 논문에서는 의료정보 2차 활용을 위한 비식별화 지침을 제공하고 있는 미국의 HIPAA(Health Insurance Portability and Accountability Act) Privacy Rule, 국내 의료기관 개인정보보호 가이드라인과 국내에서 연구된 문헌들 그리고 영국과 일본에서 제시하는 의료정보 활용 방안 대해 알아보고, 각각에서 제시하는 비식별화 대상 정보를 비교하여 국내 환경에 적합한 새로운 비식별화 대상 정보를 제안하고 향후 연구 방향을 제시한다.

• 한국융합학회논문지
• /
• 제9권10호
• /
• pp.55-59
• /
• 2018

4차 산업혁명 시대에 혁심기술인 빅데이터는 보건, 금융, 유통, 공공부문, 제조업, 마케팅 등 다양한 분야에서 서비스를 제공하고 있으며, 정확하고 신속한 데이터 분석을 통하여 마케팅 분석과 미래 설계에 매우 유용한 기술이며, 앞으로 더 발전할 가능성이 매우 높다. 하지만, 빅데이터 활용 시 가장 큰 문제점이 개인정보 보호와 프라이버시 문제이다. 빅데이터를 이용하여 분석을 통해 기존에 알지 못했던 개인의 취향 및 행동을 분석될 수도 있고, 이러한 정보들은 개인의 민감한 정보이자 개인의 프라이버시 침해가 될 수 있다. 따라서 본 논문에서는 빅데이터 환경에서 개인정보를 활용할 때 발생 가능한 개인정보 침해에 대한 필요 사항들을 분석하여, 그에 따른 필요한 개인정보보호 기술을 제안하여 개인정보 보호와 사생활 보호에 기여하고자 한다.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2015년도 추계학술발표대회
• /
• pp.763-766
• /
• 2015

Smart Healthcare System as an Open Platform (Shesop) is an integrated healthcare system and have several features, one of them is Steppy Application. Steppy does count your step and display on Shesop website. In this system security issues are not properly addressed, while Personal Health Record (PHR) patient stored in the cloud platform could be at risk. In fact, the huge electronic information available online, people needs reliable and effective technique for privacy preserving. In order to improve the security of data which are displayed on the Shesop website, so that anyone who access could not tamper without permission. Recently Xu et al. showed a pseudonym scheme using smart card as a solution in e-health systems which uses discrete logarithm problem with cyclic group. In this paper, we adopt their scheme and use it application into smartphone using Near Field Communication (NFC) to construct security in Steppy apps.

• 한국IT서비스학회지
• /
• 제11권sup호
• /
• pp.27-39
• /
• 2012

As many applications are possible now in mobile environment with the trend of mobile convergence, diverse applications in healthcare industry are also possible in mobile devices. Though lots of researches on mobile and health services are introduced, they are limited to specific area or techniques. This study shows possible directions of fusion between mobile technologies and health services in the future using a data mining technique called association rule analysis. The data used in this study is collected from web pages containing key words related to mobile technologies and health services. The analysis shows that current cases of fusion between monitoring based telemedicine and patients. It also shows another case of fusion between mobile hospital and medical screen charts. These show that fusion between mobile technologies and health services already began in industry. Association rules are found between well-being, city, diet, and sleep. The association rules containing security and privacy, though their associations are not so strong, also show that security and privacy of patient information should be protected in the future. The results show that the fusion of mobile technologies and health services is expected to provide health services to more users and larger areas. It is also expected to create new diverse business models in the future.

• Asia pacific journal of information systems
• /
• 제21권3호
• /
• pp.71-96
• /
• 2011

Within the traditional medical delivery system, patients residing in medically vulnerable areas, those with body movement difficulties, and nursing facility residents have had limited access to good healthcare services. However, Information and Communication Technology (ICT) provides us with a convenient and useful means of overcoming distance and time constraints. ICT is integrated with biomedical science and technology in a way that offers a new high-quality medical service. As a result, rapid technological advancement is expected to play a pivotal role bringing about innovation in a wide range of medical service areas, such as medical management, testing, diagnosis, and treatment; offering new and improved healthcare services; and effecting dramatic changes in current medical services. The increase in aging population and chronic diseases has caused an increase in medical expenses. In response to the increasing demand for efficient healthcare services, a telehealth service based on ICT is being emphasized on a global level. Telehealth services have been implemented especially in pilot projects and system development and technological research. With the service about to be implemented in earnest, it is necessary to study its overall acceptance by consumers, which is expected to contribute to the development and activation of a variety of services. In this sense, the study aims at positively examining the structural relationship among the acceptance factors for telehealth services based on the Technology Acceptance Model (TAM). Data were collected by showing audiovisual material on telehealth services to online panels and requesting them to respond to a structured questionnaire sheet, which is known as the information acceleration method. Among the 1,165 adult respondents, 608 valid samples were finally chosen, while the remaining were excluded because of incomplete answers or allotted time overrun. In order to test the reliability and validity of the assessment scale items, we carried out reliability and factor analyses, and in order to explore the causal relation among potential variables, we conducted a structural equation modeling analysis using AMOS 7.0 and SPSS 17.0. The research outcomes are as follows. First, service quality, innovativeness of medical technology, and social influence were shown to affect perceived ease of use and perceived usefulness of the telehealth service, which was statistically significant, and the two factors had a positive impact on willingness to accept the telehealth service. In addition, social influence had a direct, significant effect on intention to use, which is paralleled by the TAM used in previous research on technology acceptance. This shows that the research model proposed in the study effectively explains the acceptance of the telehealth service. Second, the research model reveals that information privacy concerns had a insignificant impact on perceived ease of use of the telehealth service. From this, it can be gathered that the concerns over information protection and security are reduced further due to advancements in information technology compared to the initial period in the information technology industry, and thus the improvement in quality of medical services appeared to ensure that information privacy concerns did not act as a prohibiting factor in the acceptance of the telehealth service. Thus, if other factors have an enormous impact on ease of use and usefulness, concerns over these results in the initial period of technology acceptance may become irrelevant. However, it is clear that users' information privacy concerns, as other studies have revealed, is a major factor affecting technology acceptance. Thus, caution must be exercised while interpreting the result, and further study is required on the issue. Numerous information technologies with outstanding performance and innovativeness often attract few consumers. A revised bill for those urgently in need of telehealth services is about to be approved in the national assembly. As telemedicine is implemented between doctors and patients, a wide range of systems that will improve the quality of healthcare services will be designed. In this sense, the study on the consumer acceptance of telehealth services is meaningful and offers strong academic evidence. Based on the implications, it can be expected to contribute to the activation of telehealth services. Further study is needed to assess the acceptance factors for telehealth services, such as motivation to remain healthy, health care involvement, knowledge on health, and control of health-related behavior, in order to develop unique services according to the categorization of customers based on health factors. In addition, further study may focus on various theoretical cognitive behavior models other than the TAM, such as the health belief model.

• International Journal of Internet, Broadcasting and Communication
• /
• 제15권4호
• /
• pp.261-269
• /
• 2023

We propose to design a Holochain-based security and privacy protection system for resource-constrained IoT healthcare systems. Through analysis and performance evaluation, the proposed system confirmed that these characteristics operate effectively in the IoT healthcare environment. The system proposed in this paper consists of four main layers aimed at secure collection, transmission, storage, and processing of important medical data in IoT healthcare environments. The first PERCEPTION layer consists of various IoT devices, such as wearable devices, sensors, and other medical devices. These devices collect patient health data and pass it on to the network layer. The second network connectivity layer assigns an IP address to the collected data and ensures that the data is transmitted reliably over the network. Transmission takes place via standardized protocols, which ensures data reliability and availability. The third distributed cloud layer is a distributed data storage based on Holochain that stores important medical information collected from resource-limited IoT devices. This layer manages data integrity and access control, and allows users to share data securely. Finally, the fourth application layer provides useful information and services to end users, patients and healthcare professionals. The structuring and presentation of data and interaction between applications are managed at this layer. This structure aims to provide security, privacy, and resource efficiency suitable for IoT healthcare systems, in contrast to traditional centralized or blockchain-based systems. We design and propose a Holochain-based security and privacy protection system through a better IoT healthcare system.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제18권4호
• /
• pp.826-842
• /
• 2024

As 5G and AI continue to develop, there has been a significant surge in the healthcare industry. The COVID-19 pandemic has posed immense challenges to the global health system. This study proposes an FL-supported edge computing model based on federated learning (FL) for predicting clinical outcomes of COVID-19 patients during hospitalization. The model aims to address the challenges posed by the pandemic, such as the need for sophisticated predictive models, privacy concerns, and the non-IID nature of COVID-19 data. The model utilizes the FATE framework, known for its privacy-preserving technologies, to enhance predictive precision while ensuring data privacy and effectively managing data heterogeneity. The model's ability to generalize across diverse datasets and its adaptability in real-world clinical settings are highlighted by the use of SHAP values, which streamline the training process by identifying influential features, thus reducing computational overhead without compromising predictive precision. The study demonstrates that the proposed model achieves comparable precision to specific machine learning models when dataset sizes are identical and surpasses traditional models when larger training data volumes are employed. The model's performance is further improved when trained on datasets from diverse nodes, leading to superior generalization and overall performance, especially in scenarios with insufficient node features. The integration of FL with edge computing contributes significantly to the reliable prediction of COVID-19 patient outcomes with greater privacy. The research contributes to healthcare technology by providing a practical solution for early intervention and personalized treatment plans, leading to improved patient outcomes and efficient resource allocation during public health crises.

• 한국정보통신학회:학술대회논문집
• /
• 한국해양정보통신학회 2009년도 추계학술대회
• /
• pp.866-870
• /
• 2009

Mobile Health (M-Health) system is a recent term for medical and public health practice supported by mobile devices, such as mobile phones, PDAs, and other wireless devices. Mobile Health system has been successfully establishing at few general hospital in Korea. However, to use diverse devices manufactured by various company cause inoperability, and lack of security disappoints customers often. Although the outstanding health environment, most of hospitals are unavailable to share electronic patient records due to lack of standard protocol to handle the interoperability each other. Health Level 7 (HL7) is the best solution for the problem. In this paper, we will analyse a current M-Health service in terms of security and mobile device, and suggest iPhone for the best device against hospital environment. Also, for keep confidentiality of health information and patient privacy, enhanced security mechanism is introduced. As a consequence, interoperable standard, and most appropriate device for supporting staffs and M-Health performance, and enhanced securirty mechanism will be integrated in order to propose improved M-health model.

• Asia pacific journal of information systems
• /
• 제29권4호
• /
• pp.817-837
• /
• 2019

The medical industry is rapidly evolving into a combination of artificial intelligence (AI) and ICT technology, such as mobile health, wireless medical, telemedicine and precision medical care. Medical artificial intelligence can be diagnosed and treated, and autonomous surgical robots can be operated. For smart medical services, data such as medical information and personal medical information are needed. AI is being developed to integrate with companies such as Google, Facebook, IBM and others in the health care field. Telemedicine services are also becoming available. However, security issues of medical information for smart medical industry are becoming important. It can have a devastating impact on life through hacking of medical devices through vulnerable areas. Research on medical information is proceeding on the necessity of privacy and privacy protection. However, there is a lack of research on the practical measures for protecting medical information and the seriousness of security threats. Therefore, in this study, we want to confirm the research trend by collecting data related to medical information in recent 5 years. In this study, smart medical related papers from 2014 to 2018 were collected using smart medical topics, and the medical information papers were rearranged based on this. Research trend analysis uses topic modeling technique for topic information. The result constructs topic network based on relation of topics and grasps main trend through topic.