• Smart Media Journal
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• v.12 no.9
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• pp.9-18
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• 2023

Black box cryptography is a cryptographic scheme based on a hardware encryption device, operating under the assumption that the device and the user can be trusted. However, with the increasing use of cryptographic algorithms on unreliable open platforms, the threats to black box cryptography systems have become even more significant. As a consequence, white box cryptography have been proposed to securely operate cryptographic algorithms on open platforms by hiding encryption keys during the encryption process, making it difficult for attackers to extract the keys. However, unlike traditional cryptography, white box-based encryption lacks established specifications, making challenging verify its structural security. To promote the safer utilization of white box cryptography, CHES organizes The WhibOx Contest periodically, which conducts safety analyses of various white box cryptographic techniques. Among these, the Differential Computation Analysis (DCA) attack proposed by Bos in 2016 is widely utilized in safety analyses and represents a powerful attack technique against robust white box block ciphers. Therefore, this paper analyzes the research trends in white box block ciphers and provides a summary of DCA attacks and relevant countermeasures. adhering to the format of a research paper.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.129-136
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• 2023

The government of the Republic of Korea is conducting quality management of public open data by conducting a public data quality management level evaluation. Public open data is provided in various open formats such as XML, JSON, and CSV, with CSV format accounting for the majority. When diagnosing the quality of public open data in CSV format, the quality diagnosis manager determines and diagnoses the domain for each field based on the field name and data within the field of the public open data file. However, it takes a lot of time because quality diagnosis is performed on large amounts of open data files. Additionally, in the case of fields whose meaning is difficult to understand, the accuracy of quality diagnosis is affected by the quality diagnosis person's ability to understand the data. This paper proposes a domain discrimination model for public open data in CSV format using field names and data distribution statistics to ensure consistency and accuracy so that quality diagnosis results are not influenced by the capabilities of the quality diagnosis person in charge, and to support shortening of diagnosis time. As a result of applying the model in this paper, the correct answer rate was about 77%, which is 2.8% higher than the file format open data diagnostic tool provided by the Ministry of Public Administration and Security. Through this, we expect to be able to improve accuracy when applying the proposed model to diagnosing and evaluating the quality management level of public data.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.11a
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• pp.116-118
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• 2023

In recent years, the need for economical and sustainable ship routing has emerged due to the enforced regulations on environmental issues. Despite the development of weather forecasting technology, maritime accidents by rough waves have continued to occur due to incorrect weather forecasts. In this study, onboard measurements are conducted to observe the acutal situation on merchant ships in operation encountering rough waves. The types of measured data include information related to navigation (Ship's position, speed, bearing, rudder angle) and engine (engine revolutions, power, shaft thrust, fuel consumption), weather conditions (wind, waves), and ship motions (roll, pitch, and yaw). These ship experiments was conducted to 28,000 DWT bulk carrier, 63,000 DWT bulk carrier, 20,000 TEU container ship, and 12,000 TEU container ship. The actual ship experiment of each ship is intended to acquire various types of data and utilize them for multi-objective studies related to ship operation. Additionally, in order to confirm the sea conditions, the directional wave spectrum was reproduced using a wave simulation model. Through data collection from ship experiments and wave simulations, various studies could be proceeding such as the measurement for accurate wave information by marine radar and analysis for cargo collapse accidents. In addition, it is expected to be utilized in various themes from the perspective of safety and efficiency in ship operation.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.899-910
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• 2023

The majority of research on lifestyle has been conducted based on a variable-centered approach. However, over the last decades, there is a growing body of research on lifestyle in terms of a person-centered approach. Hence, this study identifies senior generations' profiles based on the combination of the five realms of lifestyle. More specifically, this study utilized a Latent profile analysis(LPA) to explore both quantitatively and qualitatively distinct types of senior generation' lifestyle profiles. As a result, the five distinct types of senior lifestyle profiles were identified and these five profiles were then contrasted with traveling attitude and behavioral intention(traveling intention). In addition, this study attempted to identify similarity in the patterns of relations with theoretical antecedent, correlate and outcome variables. Results showed that even though senior generation belonging to profile groups pertaining to the high level of all five types of lifestyle were associated with a high level of attitude and behavior intention, there was no differences among the profiles. This means that regardless of the patterns of senor generation lifestyle profiles, there was no similarity. Nevertheless, it should be considered that senior generation consider a security when making a travel ling decision regardless of the patterns of lifestyle profiles. This results suggest that senior generation' traveling satisfaction is more likely obtained with the experience of safety and convenience during their travel. At last, this study discusses some implication tourism theory related to lifestyle, practices and future research on tourism profiles.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.147-155
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• 2024

Currently, the 4th Industrial Revolution, like other revolutions, is bringing great change and new life to humanity, and in particular, the demand for and use of drones, which can be applied by combining various technologies such as big data, artificial intelligence, and information and communications technology, is increasing. Recently, it has been widely used to carry out dangerous military operations and missions, such as the Russia-Ukraine war and North Korea's reconnaissance against South Korea, and as the demand for and use of drones increases, concerns about the safety and security of drones are growing. Currently, a variety of research is being conducted, such as detection of wireless communication abnormalities and sensor data abnormalities related to drones, but research on real-time detection of threats using radio frequency characteristic data is insufficient. Therefore, in this paper, we conduct a study to determine whether the characteristic data is normal or abnormal signal data by collecting radio frequency signal characteristic data generated while the drone communicates with the ground control system while performing a mission in a HITL(Hardware In The Loop) simulation environment similar to the real environment. proceeded. In addition, we propose an unsupervised learning-based threat detection system and optimal threshold that can detect threat signals in real time while a drone is performing a mission.

• Journal of the Korean institute of surface engineering
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• v.57 no.1
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• pp.38-48
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• 2024

We fabricated In₂O₃ zig-zag nanocolumns(ZZNCs) by oblique angle deposition method based on e-beam evaporator for highly sensitive and selective CH₃COCH₃ sensor. Our results indicate that as the ZZNCs layer stacks, the gas response also increases. In comparison to thin films, ZZNCs at 5 layer show a 117-fold enhancement in gas response and a rapid response time (~2 s). When measured with various gases, it showed a high selectivity towards acetone. Under conditions of 80% R.H., exposure to CH₃COCH₃ gas theoretically indicated a detection limit of 1.2 part-per-billion(ppb). These results suggest the potential of In₂O₃ ZZNCs as a breath analyzer for the diagnosis of diabetes.

• Journal of Korean Society of Archives and Records Management
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• v.24 no.2
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• pp.89-112
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• 2024

Metadata is a crucial component of record management, playing a vital role in properly managing and understanding the record. In cases where automatic metadata assignment is not feasible, manual input by records professionals becomes necessary. This study aims to alleviate the challenges associated with manual entry by proposing a method that harnesses ChatGPT technology for extracting records management metadata elements. To employ ChatGPT technology, a Python program utilizing the LangChain library was developed. This program was designed to analyze PDF documents and extract metadata from records through questions, both with a locally installed instance of ChatGPT and the ChatGPT online service. Multiple PDF documents were subjected to this process to test the effectiveness of metadata extraction. The results revealed that while using LangChain with ChatGPT-3.5 turbo provided a secure environment, it exhibited some limitations in accurately retrieving metadata elements. Conversely, the ChatGPT-4 online service yielded relatively accurate results despite being unable to handle sensitive documents for security reasons. This exploration underscores the potential of utilizing ChatGPT technology to extract metadata in records management. With advancements in ChatGPT-related technologies, safer and more accurate results are expected to be achieved. Leveraging these advantages can significantly enhance the efficiency and productivity of tasks associated with managing records and metadata in archives.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.183-192
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• 2024

The purpose of this study is to empirically analyze the determining factors (economy, security, domestic politics, administration, and international politics) that affect the ROK-US defense cost sharing decision. Through this, we will gain a deeper understanding of the defense cost sharing decision process and improve the efficiency of defense cost sharing calculation and execution. The scope of the study is ROK-US defense cost sharing from 1991 to 2021. The data used in the empirical analysis were various secondary data such as Ministry of National Defense, government statistical data, SIPRI, and media reports. As an empirical analysis method, multiple regression analysis using time series was used and the data was analyzed using an autoregressive model. As a result of empirical research through multiple regression analysis, we derived the following results. It was analyzed that the size of Korea's economy, that is, GDP, the previous year's defense cost share, and the number of U.S. troops stationed in Korea had a positive influence on the decision on defense cost sharing. This indicates that Korea's economic growth is a major factor influencing the increase in defense cost sharing, and that the gradual increase in the budget and the negotiation method of the Special Agreement (SMA) for cost sharing of stationing US troops in Korea play an important role. On the other hand, the political tendencies of the ruling party, North Korea's military threats, and China's defense budget were found to have no statistically significant influence on the decision to share defense costs.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.19-24
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• 2024

The future military combat environment is rapidly expanding the role and importance of artificial intelligence (AI) in defense, aligning with the current trends of declining military populations and evolving dynamics. Particularly, in the civilian sector, AI development has surged into new domains based on foundation models, such as OpenAI's Chat-GPT, categorized as Super-Giant AI or Hyperscale AI. The U.S. Department of Defense has organized Task Force Lima under the Chief Digital and AI Office (CDAO) to conduct research on the application of Large Language Models (LLM) and generative AI. Advanced military nations like China and Israel are also actively researching the integration of Super-Giant AI into their military capabilities. Consequently, there is a growing need for research within our military regarding the potential applications and fields of application for Super-Giant AI in weapon systems. In this paper, we compare the characteristics and pros and cons of specialized AI and Super-Giant AI (Foundation Models) and explore new application areas for Super-Giant AI in weapon systems. Anticipating future application areas and potential challenges, this research aims to provide insights into effectively integrating Super-Giant Artificial Intelligence into defense operations. It is expected to contribute to the development of military capabilities, policy formulation, and international security strategies in the era of advanced artificial intelligence.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.891-899
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• 2024

The Fourth Industrial Revolution is centered on a personalized demand fulfillment economy and is all about transformation and flexible processing that can deliver what customers want in real time across space and time. This paper implements the construction and operation of a packaging platform that can instantly procure the required packaging products based on real-time orders and evaluates its performance. The components of customer satisfaction are flexible and dependent on the situation which requires efficient management of enterprise operational processes based on an e-SCM platform. An OMS optimized for these conditions plays an important role in maximizing and differentiating the efficiency of a company's operations and improving its cost advantage. OMS is a system of mass customization that provides efficient MOT(Moment of Truth) logistics services to meet the eco-friendly issues of many individual customers and achieve optimized logistics operation goals to enhance repurchase intentions and sustainable business. OMS precisely analyzes the collected data to support information and decision-making related to efficiency, productivity, cost and provide accurate reports. It uses data visualization tools to express data visually and suggests directions for improvement of the operational process through statistics and prediction analysis.