• The Journal of Society for e-Business Studies
• /
• v.26 no.2
• /
• pp.123-141
• /
• 2021

As the dependence of technology on the economic structure increases, the importance of National Core Technology is increasing. However, due to the nature of the technology itself, it is difficult to determine the scope of the technology to be protected because the scope of the relation is abstract and information disclosure is limited due to the nature of the National Core Technology. To solve this problem, we propose the most appropriate literature type and method of analysis to distinguish important technologies related to National Core Technology. We conducted a pilot test to apply TF-IDF, and LDA topic modeling, two techniques of text mining analysis for big data analysis, to four types of literature (news, papers, reports, patents) collected with National Core Technology keywords in the field of Display industry. As a result, applying LDA theme modeling to patent data are highly relevant to National Core Technology. Important technologies related to the front and rear industries of displays, including OLEDs and microLEDs, were identified, and the results were visualized as networks to clarify the scope of important technologies associated with National Core Technology. Throughout this study, we have clarified the ambiguity of the scope of association of technologies and overcome the limited information disclosure characteristics of national core technologies.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.8 no.6
• /
• pp.835-844
• /
• 2018

Recently, as the number of smartphone users has been increasing worldwide, various services such as electronic payment, internet use, and financial settlement are being used as a smartphone. In addition, researches for home appliance control and automobile control using smartphone are conducted. As such, smartphone users can enjoy a more convenient life, but by hacking smartphones, tapping texts and conversations on smartphones, tracking location through spy apps, DDoS attacks using smartphones, and malicious apps When a message is received at a specific telephone number when using a micropayment, the corresponding text message is transmitted to a remote server, thereby increasing the risk of leakage of personal information and the like. Therefore, in this paper, we define the risk factors of the smartphone that are caused by the internal and external environmental, physical, contents (apps) of the smartphone through the smartphone that we use in real life, We propose a method to check vulnerability of smartphone security solution such as CC evaluation and the most effective response technique for each risk of smartphone by defining the technique.

• Journal of Service Research and Studies
• /
• v.14 no.1
• /
• pp.13-26
• /
• 2024

Multi-modal generation is the process of generating results based on a variety of information, such as text, images, and audio. With the rapid development of AI technology, there is a growing number of multi-modal based systems that synthesize different types of data to produce results. In this paper, we present an AI system that uses speech and text recognition to describe a person and generate a montage image. While the existing montage generation technology is based on the appearance of Westerners, the montage generation system developed in this paper learns a model based on Korean facial features. Therefore, it is possible to create more accurate and effective Korean montage images based on multi-modal voice and text specific to Korean. Since the developed montage generation app can be utilized as a draft montage, it can dramatically reduce the manual labor of existing montage production personnel. For this purpose, we utilized persona-based virtual person montage data provided by the AI-Hub of the National Information Society Agency. AI-Hub is an AI integration platform aimed at providing a one-stop service by building artificial intelligence learning data necessary for the development of AI technology and services. The image generation system was implemented using VQGAN, a deep learning model used to generate high-resolution images, and the KoDALLE model, a Korean-based image generation model. It can be confirmed that the learned AI model creates a montage image of a face that is very similar to what was described using voice and text. To verify the practicality of the developed montage generation app, 10 testers used it and more than 70% responded that they were satisfied. The montage generator can be used in various fields, such as criminal detection, to describe and image facial features.

• Informatization Policy
• /
• v.23 no.3
• /
• pp.26-42
• /
• 2016

Recently, with the rapid growth of the O2O market, Fintech combining the finance and ICT technology is drawing attention as innovation to lead "O2O of finance", along with Fintech-based payment, authentication, security technology and related services. For new technology industries such as Fintech, technical sources, related systems and regulations are important but previous studies on Fintech lack in-depth research about systems and technological trends of the domestic Fintech industry. Therefore, this study aims to analyze domestic Fintech trends and find the insights for the direction of technology and systems of the future domestic Fintech industry by comparing Kakao Pay and Samsung Pay, the two domestic representative mobile payment services. By conducting a complete enumeration survey about the tweets mentioning Fintech until June 2016, this study visualized topics extraction, sensitivity analysis and keyword analyses. According to the analysis results, it was found that various topics have been created in the technologies and systems between 2014 and 2016 and different keywords and reactions were extracted between topics of Samsung Pay based on "devices" such as Galaxy and Kakao Pay based on "service" such as KakaoTalk. This study contributes to analyzing the unstructured data of social media by period by using social media mining and quantifying the expectations and reactions of consumers to services through the sentiment analysis. It is expected to be the foundation of Fintech industry development by presenting a strategic direction to Fintech related practitioners.

• Journal of Intelligence and Information Systems
• /
• v.22 no.4
• /
• pp.87-107
• /
• 2016

Understanding market convergence has became essential for small and mid-size enterprises. Identifying convergence items among heterogeneous markets could lead to product innovation and successful market introduction. Previous researches have two limitations. First, traditional researches focusing on patent databases are suitable for detecting technology convergence, however, they have failed to recognize market demands. Second, most researches concentrate on identifying the relationship between existing products or technology. This study presents a platform to identify the opportunity of market convergence by using product databases from a global B2B marketplace. We also attempt to identify convergence opportunity in different industries by applying Structural Hole theory. This paper shows the mechanisms for market convergence: attributes extraction of products and services using text mining and association analysis among attributes, and network analysis based on structural hole. In order to discover market demand, we analyzed 240,002 e-catalog from January 2013 to July 2016.

• Journal of Digital Convergence
• /
• v.15 no.4
• /
• pp.285-293
• /
• 2017

They are rapidly evolving malicious attacks on smart devices, and to timely protect the smart devices from these attacks has become a very important issue. In particular, smishing attack has emerged as one of the most important threats on the smartphone. In this paper, we propose the cloud service that can fundamentally protect the user from the risk of smishing attack. The proposed scheme provides cloud messaging service that can filter text messages including URLs in the user's smart device, view and manage them through a virtual machine provided by a cloud server. The existing techniques for preventing smshing attacks protect only malicious code of a known pattern and there is the possibility of error such as FP(False Positive) or FN(False Negative). However, since the proposed method automatically filters all text messages including URLs, storing, viewing, and managing them in their own storage space on the cloud server, it can completely block the installation of malwares(malicious codes) on the user's smart device through smishing attacks.

• Journal of Digital Convergence
• /
• v.19 no.2
• /
• pp.1-12
• /
• 2021

With the recent 4th Industrial Revolution, the growth and value of big data are continuously increasing, and the government is also actively making efforts to open and utilize public data. However, the situation still does not reach the level of demand for public data use by citizens, At this point, it is necessary to identify research trends in the public data field and seek directions for development. In this study, in order to understand the research trends related to public data, the analysis was performed using topic modeling, which is mainly used in text mining techniques. To this end, we collected papers containing keywords of 'Public data' among domestic and foreign research papers (1,437 domestically, 9,607 overseas) and performed topic modeling based on the LDA algorithm, and compared domestic and foreign public data research trends. After analysis, policy implications were presented. Looking at the time series by topic, research in the fields of 'personal information protection', 'public data management', and 'urban environment' has increased in Korea. Overseas, it was confirmed that research in the fields of 'urban policy', 'cell biology', 'deep learning', and 'cloud·security' is active.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.2
• /
• pp.109-118
• /
• 2024

With the increasing number of social media users worldwide, cases of social media being abused to perpetrate various crimes are increasing. Specifically, drug distribution through social media is emerging as a serious social problem. Using social media channels, the curiosity of teenagers regarding drugs is stimulated through clever marketing. Further, social media easily facilitates drug purchases due to the high accessibility of drug sellers and consumers. Among various social media platforms, we focused on Instagram, which is the most used social media platform by young adults aged 19 to 24 years in South Korea. We collected four types of information, including profile photos, introductions, posts in the form of images, and posts in the form of texts on Instagram; then, we analyzed the similarity among each type of collected information. The profile photos and posts in the form of image were analyzed for similarity based on the SSIM(Structural Simplicity Index Measure), while introductions and posts in the form of text were analyzed for similarity using Jaccard and Cosine similarity techniques. Through the similarity analysis, the similarity among various accounts for each collected information type was measured, and accounts with similarity above the significance level were determined as the same drug sales account. By performing logistic regression analysis on the aforementioned information types, we confirmed that except posts in image form, profile photos, introductions, and posts in the text form were valid information for tracking the same drug sales account.

• Tuberculosis and Respiratory Diseases
• /
• v.40 no.5
• /
• pp.595-601
• /
• 1993

Background: Today, tuberculosis continues as an important cause of death in Korea despite the effective treatment and prevention. So we have studied charicteristic distribution of death by pulmonary tuberculosis through epidemiologic survey. Subjects and Method: The mortality data were obtained from 684 pulmonary tuberculosis cases who died in a tuberculosis-centered hospital in Seoul during the period of 5 years from 1986 to 1990. In order to estimate the distribution of death by tuberculosis, t-test and $x^2$-text were performed on the data. Results: 1) 19.9% of patients died among the total 3,441 hospitalized pulmonary tuberculosis cases during 5 years. 2) In distribution of sex and age, male death occupies 81% of total death. Significantly high proportions of younger female death (under 40 years-old) were also observed. 3) In terms of medical security status, medical assistance group occupies 42.3% of medical insurance group while the non-security group also occupies 11.8% of total death. 4) Treatment interruption was observed in 78% of total death. Conclusion: Special attention should be given to the identification, management and follow up of high risk group in nationwide tuberculosis control program.

• Journal of the Korea Society of Computer and Information
• /
• v.18 no.11
• /
• pp.39-49
• /
• 2013

In this paper, security mechanism of internal network(CAN) of vehicle is a very incomplete state and the possibility of external threats as a way to build a test environment that you can easily buy from the market by the vehicle's ECU(Electric Control Unit) to verify and obtain a CAN message. Then, by applying it to ECU of the real car to try to attack is proposed. A recent study, Anyone can see plain-text status of the CAN message in the vehicle. so that in order to verify the information is vulnerable to attack from outside, analyze the data in a vehicle has had a successful attack, but attack to reverse engineering in the stationary state and buying a car should attempt has disadvantages that spatial, financial, and time costs occurs. Found through the car's ECU CAN message is applied to a real car for Potential threats outside of the car to perform an experiment to verify and equipped with a wireless network environment, the experimental results, proposed method through in the car to make sure the attack is possible. As a result, reduce the costs incurred in previous studies and in the information absence state of the car, potential of vehicle's ECU attack looks.