• Korea Trade Review
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• v.48 no.3
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• pp.243-262
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• 2023

This study provides a systematic review of smart trade contracts, examining the research trends and theoretical background of utilizing smart contracts and blockchain technology for the digitalization and automation of trade contracts. Smart trade contracts are a concept that applies the automated contract system based on blockchain to trade-related transactions. The study analyzes the technical and legal challenges and proposes solutions. The technical aspect covers the development of smart contract platforms, scalability and performance improvements of blockchain networks, and security and privacy concerns. The legal aspect addresses the legal enforceability of smart contracts, automatic execution of contract conditions, and the responsibilities and obligations of contract parties. Smart trade contracts have been found to have applications in various industries such as international trade, supply chain management, finance, insurance, and energy, contributing to the ease of trade finance, efficiency of supply chains, and business model innovation. However, challenges remain in terms of legal regulations, interaction with existing legal frameworks, and technological aspects. Further research is needed, including empirical studies, business model innovation, resolution of legal issues, security and privacy considerations, standardization and collaboration, and user experience studies to address these challenges and explore additional aspects of smart trade contracts.

• Convergence Security Journal
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• v.23 no.3
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• pp.57-64
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• 2023

Due to the COVID-19 pandemic, the broadcasting industry has been greatly affected, to the extent that the footprint of travel programs has disappeared. Although travel programs have been back on the air since 2022, there remains a task of recovering the stagnant desire for travel. Based on a study that travel programs have a positive impact on viewers' travel intentions, this study examined a data service that provides preferred additional information on travel programs, considering the broadcasting environment of satellite broadcasters that transmit multiple travel programs through various channels. Specifically, preferred additional information was investigated for travel programs of various genres and formats, and a feature model based on FODA was designed to be used when the satellite broadcaster decides the data service configuration. In addition, the necessary information for operating the data service was defined based on the feature model, and a method of transmitting it using the DVB-S SI, a domestic satellite broadcasting standard, was devised. The feasibility of this study was also confirmed using a DVB-MHP based data service prototype.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.3
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• pp.23-40
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• 2024

Hardware attacks involve physical reverse engineering efforts to steal sensitive information, such as encryption keys and circuit designs. Encryption and obfuscation are representative countermeasures, but they are nullified if adversaries manage to find the key. To address this issue, we propose e-Cryptex, which utilizes a Physically Unclonable Function (PUF) as an anti-tampering shield. PUF acts as a random number generator and relies on unique physical variants that cannot be replicated or restored to enhance anti-tampering mechanisms. e-Cryptex uses PUF as a shield to protect the system's structure and generate the key. Tampering with the shield will result in the destruction of the key. This paper demonstrates that e-Cryptex meets PUF security requirements and is effective in detecting of tampering attempts that pierce or completely destroy the shield. Each board consistently generates the same key under normal conditions, while also showing key uniqueness across different boards.

• 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 Platform Technology
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• v.12 no.2
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• pp.12-22
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• 2024

With the rapid increase in digital data in modern society, digital forensics plays a crucial role, and file type identification is one of its integral components. Research on the development of identification models utilizing artificial intelligence is underway to identify file types swiftly and accurately. However, existing studies do not support the identification of file types with high domestic usage rates, making them unsuitable for use within the country. Therefore, this paper proposes a more accurate file type identification model using Convolutional Neural Networks (CNN) and Gated Recurrent Units (GRU). To overcome limitations of existing methods, the proposed model demonstrates superior performance on the FFT-75 dataset, effectively identifying file types with high domestic usage rates such as HWP, ALZ, and EGG. The model's performance is validated by comparing it with three existing research models (CNN-CO, FiFTy, CNN-LSTM). Ultimately, the CNN and GRU based file type identification and classification model achieved 68.2% accuracy on 512-byte file fragments and 81.4% accuracy on 4096-byte file fragments.

• Journal of Korea Port Economic Association
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• v.39 no.4
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• pp.67-82
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• 2023

This study clarified a complicated cause-and-effect relationship about the manpower utilization of container terminals. This paper conducted confirmatory factor analysis and structural equation modeling using 5 factors: technology development, safety and security change, external environment, terminal operation, and organizational culture that have been derived in the first study(2021). The results imply that technology development and external environment have a direct effect while terminal operation and safety and security change have indirect effect on a manpower utilization of container terminals. Based on these results, this paper may provide various policy implications for port operators, developers, and managers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.514-523
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• 2021

Recently, the proliferation of mobile simple payment services has been increasingly affecting people's lives. In addition, the increase in research from both China and Korea shows that the continuous development of simple mobile payment services will be very important in the future. The blog posts mentioning Kakao Pay and Alipay were collected, and keyword analysis was performed to investigate differences in consumers' responses to Kakao Pay and Alipay on social media. The frequency of keywords for each part of speech and the frequency of co-occurred words mentioned in one sentence were analyzed. Specifically, common words that appear in both Kakao Pay and Alipay blogs were extracted. The cooccurred words were analyzed to examine how different reactions were made on the same subject. As a result of the analysis, there were concerns among consumers about the trust of Kakao Pay and Alipay's benefits. For a mobile payment service to become competitive, it is necessary to add various additional services or solve security problems.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.3
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• pp.91-98
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• 2021

Today's information and communication technology is rapidly developing, the security of IT infrastructure is becoming more important, and at the same time, cyber attacks of various forms are becoming more advanced and sophisticated like intelligent persistent attacks (Advanced Persistent Threat). Early defense or prediction of increasingly sophisticated cyber attacks is extremely important, and in many cases, the analysis of network-based intrusion detection systems (NIDS) related data alone cannot prevent rapidly changing cyber attacks. Therefore, we are currently using data generated by intrusion detection systems to protect against cyber attacks described above through Host-based Intrusion Detection System (HIDS) data analysis. In this paper, we conducted a comparative study on machine learning algorithms using LID-DS (Leipzig Intrusion Detection-Data Set) host-based intrusion detection data including thread information, metadata, and buffer data missing from previously used data sets. The algorithms used were Decision Tree, Naive Bayes, MLP (Multi-Layer Perceptron), Logistic Regression, LSTM (Long Short-Term Memory model), and RNN (Recurrent Neural Network). Accuracy, accuracy, recall, F1-Score indicators and error rates were measured for evaluation. As a result, the LSTM algorithm had the highest accuracy.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.404-415
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• 2022

The purpose of this study is to propose considerations to help actual application based on the characteristics of the online art-based peer supervision execution process. Colleagues in the clinical art therapy doctoral program, including the researcher, attempted to repeatedly identify problems and apply improvements in the implementation process as research participants, and qualitatively analyzed the various data collected in the process. Looking at the characteristics of the analysis results, extensibility of materials and space was confirmed in terms of 'art-based' and initiative, convenience, and speed in terms of 'online'. The considerations identified through this are as follows. First, 'pre-structuring' should be based on clear boundaries and setting, prior consultation of the group, and self-directed preparation and attitude. Second, for the 'structural aspect of art', space and media to help immersion through creation, and stable implementation structure should be established. Third, in the 'technical aspect', it is necessary to apply a method that can deliver a work of art and a method that can communicate the creator's clear intention. Lastly, for the 'ethical aspect', it is necessary to use online software in accordance with the minimum security standards and to make efforts to repeatedly maintain confidentiality. This study is meaningful in that it suggested a practical method for maintaining the professional competence of art therapists and expanding networks among art therapists in various situations including pandemics.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.125-134
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• 2018

Lamport firstly suggested password base authentication scheme and then, similar authentication schemes have been studied. Due to the development of Internet network technology, remote user authentication using smart card has been studied. Li et al. analyzed authentication scheme of Chen et al. and then, Li et al. found out the security weakness of Chen et al.'s scheme such forward secrecy and the wrong password login problem, and proposed an a new smart card based user password authentication scheme. But Liu et al. found out that Li et al.'s scheme still had security problems such an insider attack and man-in-the-middle attack and then Liu et al. proposed an efficient and secure smart card based password authentication scheme. This paper analyzed Liu et al.'s authentication and found out that Liu et al.'s authentication has security weakness such as no perfect forward secrecy, off-line password guessing attack, smart-card loss attack, and no anonymity. And then, this paper proposed security enhanced efficient smart card based password authentication scheme using fuzzy extraction technology.