• Convergence Security Journal
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• v.22 no.2
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• pp.59-66
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• 2022

Recently, smart home technology has been developed with a great response due to the convenience of home automation. Smart home technology provides various services by connecting various Internet of Things (IoT) and sensors to a home network through wired/wireless networks. In addition, the smart home service easily and conveniently controls lighting, energy, environment, and door cameras through a wall pad. However, while it has become a social issue due to the recent hacking accident of wall pads, personal information leakage and privacy infringement are expected. Accordingly, it is necessary to prepare preventive and countermeasures against security vulnerability factors of wall pads. Therefore, this study expects that it can be used as basic data for future smart home application and response technology development by examining the weak causes and countermeasures related to wall pads.

• Journal of Information Technology Services
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• v.22 no.5
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• pp.1-16
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• 2023

This study aimed to provide fundamental insights into the digital customer experience by identifying its components and analyzing their importance and satisfaction levels among youths. To achieve this objective, the components of digital customer experience were identified through a review of prior research and consultation with experts. Subsequently, a survey was conducted with 200 youths in Seoul and Gyeonggi-do. The main findings of the study are as follows: First, The components of the digital customer experience consisted of 12 items grouped into three categories. Second, an analysis of the disparity between the importance and satisfaction levels of digital customer experience revealed statistically significant differences across all items. Third, By utilizing IPA (Importance-Performance Analysis), the digital customer experience was categorized into four quadrant, each with its own characteristics and recommendations for management: The first quadrant, the "current level maintenance area," encompassed items related to "entertainment" and "recommended service." This area is currently functioning well but necessitates continuous attention and management. The second quadrant, the "area to be supported first," included items such as "personalization," "security," "inducing participation," "privacy," and "individuality expression." Intensive management and improvements are imperative in this quadrant. The third quadrant, the "long-term improvement area," consisted of items like 'consistency,' 'information quality,' and 'convenience.' These items require focus on long-term enhancement efforts. The fourth quadrant, the "areas where efforts have already been invested," encompassed items like 'accessibility' and 'deliberation.' It appears that excessive investment has been made in these areas relative to their importance, calling for selective investments while considering the specific issues associated with each factor. These research findings serve as essential data for managing the digital customer experiences of youths.

• Korean Journal of Radiology
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• v.22 no.12
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• pp.2073-2081
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• 2021

Deep learning-based applications have great potential to enhance the quality of medical services. The power of deep learning depends on open databases and innovation. Radiologists can act as important mediators between deep learning and medicine by simultaneously playing pioneering and gatekeeping roles. The application of deep learning technology in medicine is sometimes restricted by ethical or legal issues, including patient privacy and confidentiality, data ownership, and limitations in patient agreement. In this paper, we present an open platform, MI2RLNet, for sharing source code and various pre-trained weights for models to use in downstream tasks, including education, application, and transfer learning, to encourage deep learning research in radiology. In addition, we describe how to use this open platform in the GitHub environment. Our source code and models may contribute to further deep learning research in radiology, which may facilitate applications in medicine and healthcare, especially in medical imaging, in the near future. All code is available at https://github.com/mi2rl/MI2RLNet.

• Information Systems Review
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• v.22 no.3
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• pp.157-172
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• 2020

The demand of information security consultants is expected to increase due to the emergence of ISMS-P incorporating ISMS and PIMS, the implementation of European Privacy Act (GDPR) and various security accidents. In this paper, we collected and analyzed advertisements of job advertisement sites that could identify firms' demand explicitly. We selected representative job advertisement sites in Korea and the United States and collected job advertisement details of information security consultants in 2014 and 2019. The collected data were visualized using text mining and analyzed using non-parametric methods to determine whether there was a change in the role of the information security consultant. The findings show that the requirements for information security consultants have changed very little. This means that the role does not change much over a five year time gap. The results of the study are expected to be helpful to policy makers related to information security consultants, those seeking to find employment as information security consultants, and those seeking information security consultants.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.1-8
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• 2024

On-device AI technology, which can operate AI models at the edge devices to support real-time processing and privacy enhancement, is attracting attention. As intelligent IoT is applied to various industries, services utilizing the on-device AI technology are increasing significantly. However, general deep learning models require a lot of computational resources for inference and learning. Therefore, various lightweighting methods such as quantization and pruning have been suggested to operate deep learning models in embedded edge devices. Among the lightweighting methods, we analyze how to lightweight and apply deep learning models to edge computing devices, focusing on pruning technology in this paper. In particular, we utilize dynamic and static pruning techniques to evaluate the inference speed, accuracy, and memory usage of a lightweight AI vision model. The content analyzed in this paper can be used for intelligent video control systems or video security systems in autonomous vehicles, where real-time processing are highly required. In addition, it is expected that the content can be used more effectively in various IoT services and industries.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.4
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• pp.35-42
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• 2024

In this study, we propose a method for real-time recognition and analysis of dog behavior using a motion sensor and deep learning techonology. The existing home CCTV (Closed-Circuit Television) that recognizes dog behavior has privacy and security issues, so there is a need for new technologies to overcome them. In this paper, we propose a system that can analyze and care for a dog's behavior based on the data measured by the motion sensor. The study compares the MLP (Multi-Layer Perceptron) and CNN (Convolutional Neural Network) models to find the optimal model for dog behavior analysis, and the final model, which has an accuracy of about 82.19%, is selected. The model is lightened to confirm its potential for use in embedded environments.

• Journal of forensic and investigative science
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• v.1 no.2
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• pp.5-19
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• 2006

Data mining is an information extraction activity to discover hidden facts contained in databases. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future results. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis. Law enforcement agencies deal with mass data to investigate the crime and its amount is increasing due to the development of processing the data by using computer. Now new challenge to discover knowledge in that data is confronted to us. It can be applied in criminal investigation to find offenders by analysis of complex and relational data structures and free texts using their criminal records or statement texts. This study was aimed to evaluate possibile application of data mining and its limitation in practical criminal investigation. Clustering of the criminal cases will be possible in habitual crimes such as fraud and burglary when using data mining to identify the crime pattern. Neural network modelling, one of tools in data mining, can be applied to differentiating suspect's photograph or handwriting with that of convict or criminal profiling. A case study of in practical insurance fraud showed that data mining was useful in organized crimes such as gang, terrorism and money laundering. But the products of data mining in criminal investigation should be cautious for evaluating because data mining just offer a clue instead of conclusion. The legal regulation is needed to control the abuse of law enforcement agencies and to protect personal privacy or human rights.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.1-23
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• 2019

Big data refers to data that is difficult to store, manage, and analyze by existing software. As the lifestyle changes of consumers increase the size and types of needs that consumers desire, they are investing a lot of time and money to understand the needs of consumers. Companies in various industries utilize Big Data to improve their products and services to meet their needs, analyze unstructured data, and respond to real-time responses to products and services. The financial industry operates a decision support system that uses financial data to develop financial products and manage customer risks. The use of big data by financial institutions can effectively create added value of the value chain, and it is possible to develop a more advanced customer relationship management strategy. Financial institutions can utilize the purchase data and unstructured data generated by the credit card, and it becomes possible to confirm and satisfy the customer's desire. CRM has a granular process that can be measured in real time as it grows with information knowledge systems. With the development of information service and CRM, the platform has change and it has become possible to meet consumer needs in various environments. Recently, as the needs of consumers have diversified, more companies are providing systematic marketing services using data mining and advanced CRM (Customer Relationship Management) techniques. KB Kookmin Card, which started as a credit card business in 1980, introduced early stabilization of processes and computer systems, and actively participated in introducing new technologies and systems. In 2011, the bank and credit card companies separated, leading the 'Hye-dam Card' and 'One Card' markets, which were deviated from the existing concept. In 2017, the total use of domestic credit cards and check cards grew by 5.6% year-on-year to 886 trillion won. In 2018, we received a long-term rating of AA + as a result of our credit card evaluation. We confirmed that our credit rating was at the top of the list through effective marketing strategies and services. At present, Kookmin Card emphasizes strategies to meet the individual needs of customers and to maximize the lifetime value of consumers by utilizing payment data of customers. KB Kookmin Card combines internal and external big data and conducts marketing in real time or builds a system for monitoring. KB Kookmin Card has built a marketing system that detects realtime behavior using big data such as visiting the homepage and purchasing history by using the customer card information. It is designed to enable customers to capture action events in real time and execute marketing by utilizing the stores, locations, amounts, usage pattern, etc. of the card transactions. We have created more than 280 different scenarios based on the customer's life cycle and are conducting marketing plans to accommodate various customer groups in real time. We operate a smart offering system, which is a highly efficient marketing management system that detects customers' card usage, customer behavior, and location information in real time, and provides further refinement services by combining with various apps. This study aims to identify the traditional CRM to the current CRM strategy through the process of changing the CRM strategy. Finally, I will confirm the current CRM strategy through KB Kookmin card's big data utilization strategy and marketing activities and propose a marketing plan for KB Kookmin card's future CRM strategy. KB Kookmin Card should invest in securing ICT technology and human resources, which are becoming more sophisticated for the success and continuous growth of smart offering system. It is necessary to establish a strategy for securing profit from a long-term perspective and systematically proceed. Especially, in the current situation where privacy violation and personal information leakage issues are being addressed, efforts should be made to induce customers' recognition of marketing using customer information and to form corporate image emphasizing security.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.78-82
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• 2010

Purpose: Recently, South Korea has seen a rapidly increased incidence of both breast and thyroid cancers. As a result, the I-131 scan and lymphoscintigraphy have been performed more frequently. Although this type of diagnostic imaging is prominent in that visualizes pathological conditions, which is similar to previous nuclear diagnostic imaging techniques, there is not much anatomical information obtained. Accordingly, it has been used in different ways to help find anatomical locations by transmission scan, however the results were unsatisfactory. Therefore, this study aims to realize an imaging technique which shows more anatomical information through the fusion of gamma and realistic imaging. Materials and Methods: We analyzed the data from patients who were examined by the lymphoscintigraphy and I-131 additional scan by Symbia Gamma camera (SIEMENS) in the nuclear medicine department of the National Cancer Center from April to July of 2009. First, we scanned the same location in patients by using a miniature camera (R-2000) in hyVISION. Afterwards, we scanned by gamma camera. The data we obtained was evaluated based on the scanning that measures an agreement of gamma and realistic imaging by the Gamma Ray Tool fusion program. Results: The amount of radiation technicians and patients were exposed was generated during the production process of flood source and applied transmission scan. During this time, the radiation exposure dose of technicians was an average of 14.1743 ${\mu}Sv$, while the radiation exposure dose of patients averaged 0.9037 ${\mu}Sv$. We also confirmed this to matching gamma and realistic markers in fusion imaging. Conclusion: Therefore, we found that we could provide imaging with more anatomical information to clinical doctors by fusion of system of gamma and realistic imaging. This has allowed us to perform an easier method in which to reduce the work process. In addition, we found that the radiation exposure can be reduced from the flood source. Eventually, we hope that this will be applicable in other nuclear medicine studies. Therefore, in order to respect the privacy of patients, this procedure will be performed only after the patient has agreed to the procedure after being given a detailed explanation about the process itself and its advantages.

• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.93-100
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• 2021

With the spread of digital trade, the share of digital trade under the global trade environment is increasing. However, since there is no international digital trade standard, the discussion to establish a new trade rule has important significance. Countries around the world are implementing digital trade policies in consideration of their own interests, but different regulatory policies are causing trade conflicts. In order to provide safeguards against personal information infringement due to the free movement of data across borders, major countries around the world have taken measures to localize data, and the EU has enacted GDPR. And the United States regards the imposition of the digital tax as a trade barrier, and some countries oppose the implementation of the digital tax for fear of negative impact on their countries. However, discussions on the global digital tax, centered on the OECD and the G20 are making progress. As it is highly likely that a digital tax agreement will be drawn up within this year, countermeasures must also be prepared. Therefore, this study presents implications for the future direction of Korea's trade policy by examining recent trends in digital trade norms and analyzing major issues in digital trade.