• The Journal of Information Systems
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• v.26 no.2
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• pp.123-142
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• 2017

Purpose The development of the Fintech industry can be on the basis of the development in IT technologies such as Big data, IoT, cloud computing, it can be considered that the financial industry is repeating the evolution into Fintech. But the awareness of the consumers is still very low. Therefore the current dissertation, tries to deduce the suggestions for invigoration measures for Fintech by conducting an empirical study on the factors that influence the intention of reuse of Fintech on the consumer's point of view. Design/methodology/approach This study made a design of the research model by integrating the factors deducted from the Expectation Confirmation Theory. This paper empirically analyzes the impact of Continuous Usage Intention for Improvement of Fintech. The 302 survey responses were used to verify research hypotheses through covariate structural equation model. Findings According to the empirical analysis result, this study confirmed that the ultimate purpose of the Fintech service is to eliminate the social cost's waste element occurring from issue of money by not using or reducing the usage of cash. Since many Fintech users have pointed out security as the priority task, a direction for the related institutions has been proposed. Second, the content of the current dissertation will be the opportunity of broadening the perception of the current consumers that perceive Fintech as only a NFC simple payment service.

• Journal of Korea Trade
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• v.26 no.8
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• pp.1-20
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• 2022

Purpose - The paper aims to develop the theory of TAM and perceived risk through a more comprehensive and rigorous understanding of the influencing factors of the consumer's adoption of LG HomNet smart home from the perspective of trade-offs. Design/methodology - Based on the TAM and perceived risk theory, combined with the individual characteristics of consumers in the context of information technology as the external factors of the technology acceptance model, this paper constructs a theoretical model of the factors affecting the use intention of the consumer. It was empirically tested by using SEM, and survey data was collected from 458 respondents. Findings - The research results show that 9 hypotheses of the research model are supported and have reliable prediction accuracy. Consumers' perceived interest, perceived connectivity and perceived controllability have a significant positive impact on their intention to use. In addition, this paper also confirmed the mediating effect of perceived usefulness and perceived ease of use. Originality/value - Consumers are very concerned about gains and losses. Low-level performance risks, security risks, and financial risks will drive the consumer to have a stronger intention to use, and financial risks have the strongest impact. This research provides a useful implication and guidance for smart home equipment manufacturers and service providers in product and service innovation and marketing and promotion strategies.

• Journal of Information Technology Services
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• v.19 no.1
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• pp.55-69
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• 2020

The Internet cyber space has become more important as it enters the intelligent information society of the 4th Industrial Revolution beyond the information age through the development of ICT, the expansion of personalized services through mobile and SNS, the development of IoT, big data, and artificial intelligence. The Internet has formed a new paradigm in human civilization, but it has focused only on the efficiency of its functions. Therefore, various side effects such as information divide, cyber terrorism, cyber violence, hacking, and personal information leakage are emerging. In this situation, facing the intelligent information society can lead to an uncontrollable chaos. Therefore, this study classifies the cyber dysfunction of intelligent information society and analyzes social cognition, suggests cyber dysfunction standard of intelligent information society, and examines the seriousness of dysfunction, and suggests technical research directions for future technologies and services. The dysfunctional classification of the intelligent information society was classified into five areas of cyber crime and terrorism, infringement of rights, intelligent information usage culture, intelligent information reliability, and social problems by FGI methodology. Based on the classification, the social perception of current and future cyber dysfunction severity was surveyed and it showed female is more sensitive than male about the dysfunction. A GAP analysis confirmed social awareness that the future society would be more serious about AI and cyber crime

• Journal of Biomedical Engineering Research
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• v.44 no.2
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• pp.99-108
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• 2023

According to the COVID-19, development of various medical software based on IoT(Internet of Things) was accelerated. Especially, interest in a central software system that can remotely monitor and control ventilators is increasing to solve problems related to the continuous increase in severe COVID-19 patients. Since medical device software is closely related to human life, this study aims to develop central monitoring system that can remotely monitor and control multiple ventilators in compliance with medical device software development standards and to verify performance of system. In addition, to ensure the safety and reliability of this central monitoring system, this study also specifies risk management requirements that can identify hazardous situations and evaluate potential hazards and confirms the implementation of cybersecurity to protect against potential cyber threats, which can have serious consequences for patient safety. As a result, we obtained medical device software manufacturing certificates from MFDS(Ministry of Food and Drug Safety) through technical documents about performance verification, risk management and cybersecurity application.

• Annual Conference of KIPS
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• 2017.11a
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• pp.200-202
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• 2017

To improve the security of OAuth 2.0 access token transportation and satisfy the challenge of resources constraint caused by the bearer token access mechanism of the OAuth 2.0, we proposed an extensional client authentication scheme that is based on the Proof-of-Possession (PoP) token mechanism. By improving the integrity of PoP token, we bind a PoP key of a public/private key pair to the PoP token. The authorization server and the resource server can authenticate the identity of the client by verifying whether the client has the possession of the PoP token. If the client can prove that it has a PoP key that matches the PoP token, then the identity of the client can be authenticated. This experimental evaluation can confirm that this scheme effectively dealing with the issue of client identity authentication and reduce resources consumption.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3365-3383
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• 2021

The rapid growth of data has successfully promoted the development of modern information and communication technologies, which are used to process data generated by public urban departments and citizens in modern cities. In specific application areas where the ciphertext of messages generated by different users' needs to be transmitted, the concept of broadcast encryption is important. It can not only improve the transmission efficiency but also reduce the cost. However, the existing schemes cannot entirely ensure the privacy of receivers and dynamically adjust the user authorization. To mitigate these deficiencies, we propose an efficient, secure identity-based broadcast encryption scheme that achieves direct revocation and receiver anonymity, along with the analysis of smart grid solutions. Moreover, we constructed a security model to ensure wireless data transmission under cloud computing and internet of things integrated devices. The achieved results reveal that the proposed scheme is semantically secure in the random oracle model. The performance of the proposed scheme is evaluated through theoretical analysis and numerical experiments.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.458-463
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• 2023

This study presents a paper on the implementation of a Raspberry Pi-based educational smart farm system. It confirms that in a real smart farm environment, the control of temperature, humidity, soil moisture, and light intensity can be smoothly managed. It also includes remote monitoring and control of sensor information through a web service. Additionally, information about intruders collected by the Pi camera is transmitted to the administrator. Although the cost of existing smart farms varies depending on the location, material, and type of installation, it costs 400 million won for polytunnel and 1.5 billion won for glass greenhouses when constructing 0.5ha (1,500 pyeong) on average. Nevertheless, among the problems of smart farms, there are lax locks, malfunctions to automation, and errors in smart farm sensors (power problems, etc.). We believe that this study can protect crops at low cost if it is complementarily used to improve the security and reliability of expensive smart farms. The cost of using this study is about 100,000 won, so it can be used inexpensively even when applied to the area. In addition, in the case of plant cultivators, cultivators with remote control functions are sold for more than 1 million won, so they can be used as low-cost plant cultivators.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.6
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• pp.137-142
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• 2020

As research on security systems using IoT (Internet of Things) devices increases, the need for research to track the location of specific objects is increasing. The goal is to detect the movement of objects in real-time and to predict the radius of movement in short time. Many studies have been done to clearly recognize and detect moving objects. However, it does not require the sharing of information between cameras that recognize objects. In this paper, using the device information of the camera and the video information taken from the camera, the movement radius of the object is predicted and information is shared about the camera within the radius to provide the movement path of the object.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1494-1507
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• 2018

Intelligent human identification using face information has been the research hotspot ranging from Internet of Things (IoT) application, intelligent self-service bank, intelligent surveillance to public safety and intelligent access control. Since 2D face images are usually captured from a long distance in an unconstrained environment, to fully exploit this advantage and make human recognition appropriate for wider intelligent applications with higher security and convenience, the key difficulties here include gray scale change caused by illumination variance, occlusion caused by glasses, hair or scarf, self-occlusion and deformation caused by pose or expression variation. To conquer these, many solutions have been proposed. However, most of them only improve recognition performance under one influence factor, which still cannot meet the real face recognition scenario. In this paper we propose a multi-scale parallel convolutional neural network architecture to extract deep robust facial features with high discriminative ability. Abundant experiments are conducted on CMU-PIE, extended FERET and AR database. And the experiment results show that the proposed algorithm exhibits excellent discriminative ability compared with other existing algorithms.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.3
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• pp.9-23
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• 2022

This study aims to examine research trends on the Internet of Things and smart city based on papers from the United States, Japan, and Korea. We collected 7113 papers related to the Internet of Things and smart city published from 2016 to 2021 in Elsevier's Scopus. Keyword frequency and centrality analysis were performed based on the abstracts of the collected papers. We found keywords with high frequency of appearance by calculating keyword frequency and identified central research keywords through the centrality analysis by country. As a result of the analysis, research on security, machine learning, and edge computing related to the Internet of Things and smart city were the most central and highly mediating research conducted in each country. As an implication, studies related to deep learning, cybersecurity, and edge computing in Korea have lower degree centrality and betweenness centrality compared to the United States and Japan. To solve the problem it is necessary to combine these studies with various fields. The future research direction is to analyze research trends on the Internet of Things and smart city in various regions such as Europe and China.