• KIPS Transactions on Computer and Communication Systems
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• v.10 no.1
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• pp.1-6
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• 2021

Recently, incidents such as proxy surgery (unlicensed medical practice) have been reported in the media that threaten the safety of patients. Alternatives such as the introduction of operating room surveillance camera devices to prevent proxy surgery are emerging, but there are practical difficulties in implementing them due to strong opposition from the medical community. However, the social credibility of doctors is falling as incidents such as proxy surgery occur frequently. In this paper, we propose a medical staff identification system combining Beacon and iris recognition. The system adds reliability by operating on the blockchain network. The system performs primary identification by performing user authentication through iris recognition and proves that the medical staff is in the operating room through beacons. It also ensures patient trust in the surgeon by receiving beacon signals in the background and performing iris authentication at random intervals to prevent medical staff from leaving the operating room after only performing initial certification.

• Journal of Internet of Things and Convergence
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• v.7 no.2
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• pp.41-45
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• 2021

This paper proposes a video content delivery scheme for vehicles. Today, we spend a lot of time commuting to work in vehicles such as trains and cars. In addition, the number of users who enjoy video content such as YouTube and Netflix in order to appease the boredom in the vehicle is increasing rapidly. Video content requires a larger amount of data usage than text-based content. Hence, the user's mobile communication data usage increases rapidly along with the cost. The proposed video content delivery scheme downloads a lot of video content in advance when the vehicle is in a free Wi-Fi area. In this way, it is possible to play video content in a vehicle at a low cost. It is expected that the proposed scheme can be applied to the Internet of Things(IoT) for moving objects.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.1
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• pp.29-37
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• 2020

This paper implements a method of extracting an object about a dog through real-time image analysis and classifying dog behaviors from the extracted images. The Darknet YOLO was used to detect dog objects, and the Teachable Machine provided by Google was used to classify behavior patterns from the extracted images. The trained Teachable Machine is saved in Google Drive and can be used by ml5.js implemented on a node.js server. By implementing an interactive web server using a socket.io module on the node.js server, the classified results are transmitted to the user's smart phone or PC in real time so that it can be checked anytime, anywhere.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.163-170
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• 2021

As a big data is being used in various industries, big data market is expanding from hardware to infrastructure software to service software. Especially it is expanding into a huge platform market that provides applications for holistic and intuitive visualizations such as big data meaning interpretation understandability, and analysis results. Demand for big data extraction and analysis using social media such as SNS is very active not only for companies but also for individuals. However despite such high demand for the collection and analysis of social media data for user trend analysis and marketing, there is a lack of research to address the difficulty of dynamic interlocking and the complexity of building and operating software platforms due to the heterogeneity of various social media service interfaces. In this paper, we propose a method for developing a framework to operate the process from collection to extraction and classification of social media data. The proposed framework solves the problem of heterogeneous social media data collection channels through adapter patterns, and improves the accuracy of social topic extraction and classification through semantic association-based extraction techniques and topic association-based classification techniques.

• International Journal of Contents
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• v.17 no.1
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• pp.37-53
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• 2021

With the advent of the 5G era, smart phones and communications network technology have progressed, and mobile short video of people's life can be made, Of the new tools of communication, at present, China's social short video industry has shown rapid development, and the most representative of the short video app is Douyin (international version: Tiktok). Under the background of Uses and Gratifications Theory, this study discusse the relationship between Douyin users' preference degree, use motivation, use satisfaction and attention intention. This study divides the content of Douyin video into 10 categories, selects the form of an online questionnaire survey, uses SPSS software to conduct quantitative analysis of 202 questionnaires after screening, and finally draws the following conclusions: (1) The content preference degree of Douyin short video (the high group and low group) is different in users' use motivation, users' satisfaction degree and users' attention intention. ALL results are within the range of statistical significance.(2) Douyin users' video content preference degree has a positive impact on users' use motivation, users' satisfaction degree, and users' attention intention. (3) Douyin users' motivation has a positive impact on users' satisfaction and user' attention intention. (4) Douyin users' satisfaction degree has a positive impact on users' attention intention. Based on the research results, we suggest that Douyin platform pushes videos according to users' preferences. In addition, as the preference degree has an impact on users' motivation, satisfaction degree and attention intention of using the platform, it is important that the platform's focus should to pay attention to the preference degree of users. Collecting users' preferences at the early stage of users' entering the platform is a good way to learn from, and doing a good job of big data collection and management in the later operation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.240-263
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• 2021

One of the biggest challenges that the software industry is facing today is to create highly efficient applications without affecting the quality of healthcare system software. The demand for the provision of software with high quality protection has seen a rapid increase in the software business market. Moreover, it is worthless to offer extremely user-friendly software applications with no ideal security. Therefore a need to find optimal solutions and bridge the difference between accessibility and protection by offering accessible software services for defense has become an imminent prerequisite. Several research endeavours on usable security assessments have been performed to fill the gap between functionality and security. In this context, several Multi-Criteria Decision Making (MCDM) approaches have been implemented on different usability and security attributes so as to assess the usable-security of software systems. However, only a few specific studies are based on using the integrated approach of fuzzy Analytic Network Process (FANP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) technique for assessing the significant usable-security of hospital management software. Therefore, in this research study, the authors have employed an integrated methodology of fuzzy logic, ANP and TOPSIS to estimate the usable - security of Hospital Management System Software. For the intended objective, the study has taken into account 5 usable-security factors at first tier and 16 sub-factors at second tier with 6 hospital management system softwares as alternative solutions. To measure the weights of parameters and their relation with each other, Fuzzy ANP is implemented. Thereafter, Fuzzy TOPSIS methodology was employed and the rating of alternatives was calculated on the foundation of the proximity to the positive ideal solution.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.449-455
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• 2021

This paper proposes an encryption web transaction attack detection system based on the existing web application monitoring system. Although there was difficulty in detecting attacks on the encrypted web traffic because the existing web traffic security systems detect and defend attacks based on encrypted packets in the network area of the encryption section between the client and server, by utilizing the technology of the web application monitoring system, it is possible to detect various intelligent cyber-attacks based on information that is already decrypted in the memory of the web application server. In addition, since user identification is possible through the application session ID, statistical detection of attacks such as IP tampering attacks, mass web transaction call users, and DDoS attacks are also possible. Thus, it can be considered that it is possible to respond to various intelligent cyber attacks hidden in the encrypted traffic by collecting and detecting information in the non-encrypted section of the encrypted web traffic.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.165-170
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• 2021

Machine learning has recently been applied to research in most areas. This is because the results of machine learning are not determined, but the learning of input data creates the objective function, which enables the determination of new data. In addition, the increase in accumulated data affects the accuracy of machine learning results. The data collected here is an important factor in machine learning. The proposed system is a convergence system of cloud systems and local fog systems for service delivery. Thus, the cloud system provides machine learning and infrastructure for services, while the fog system is located in the middle of the cloud and the user to collect and refine data. The data for this application shall be based on the Sensitive data generated by smart devices. The machine learning technique applied to this system uses SVM algorithm for classification and RNN algorithm for status recognition.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.1-8
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• 2021

In this paper, we propose an approach that combines the technological advantages of P2P and cloud computing to support MMOGs that allowing a huge amount of users worldwide to share a real-time virtual environment. The proposed P2P system based on cloud computing can provide a greater level of scalability because their more resources are added to the infrastructure even when the amount of users grows rapidly. This system also relieves a lot of computational power and network traffic, the load on the servers in the cloud by exploiting the capacity of the peers. In this paper, we describe the concept and basic architecture of cloud computing-based P2P Systems for scalability of MMOGs. An efficient and effective provisioning of resources and mapping of load are mandatory to realize this architecture that scales in economical cost and quality of service to large communities of users. Simulation results show that by controlling the amount of cloud and user-provided resource, the proposed P2P system can reduce the bandwidth at the server while utilizing their enough bandwidth when the number of simultaneous users keeps growing.

• Journal of Information Technology Services
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• v.20 no.6
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• pp.63-81
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• 2021

Joint financial network of Korea Financial Telecommunications and Clearings Institute, which is an essential facility with a natural monopoly, maintained its closedness as monopoly/public utility model, but it has evolved in the form of open banking in order to obtain domestic fintech competitiveness in the rapidly changing digital financial ecosystem such as the acceleration of Big Blur. In accordance with digital transformation strategy of financial institutions, various ICT companies are actively participating in the financial industries, which has been exclusive to banks, through the link technology called Open API. For this reason, there has been a significant change in the financial service supply chain in which ICT companies participate as users. The level of security in the financial service supply chain is determined based on the weakest part of the individual components according to the law of minimum. In addition, there is a perceived risk of personal information and financial information leakage among the main factors that affect users' intention to accept services, and appropriate protective measures against perceived security risks can be a catalyst, which increases the acceptance of open banking. Therefore, this is a study on factors affecting the introduction of open banking to achieve financial innovation by developing an open banking security control model for financial institutions, as a protective measures to user organizations, from the perspectives of cyber financial security and customer information protection, respectively, and surveying financial security experts. It is expected, from this study, that effective information protection measures will be derived to protect the rights and interests of financial customers and will help promote open banking.