• Journal of Venture Innovation
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• v.2 no.1
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• pp.13-21
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• 2019

In LTE environment, which is 4th generation mobile communication systems, there is concern about private information exposure by transmitting initial identifier in plain text. This paper suggest mutual authentication protocol, which uses one-time password utilizing challenge-response and AES-based Milenage key generation algorithm, as solution for safe initial identification communication, preventing unique identification information leaking. Milenage key generation algorithm has been used in LTE Security protocol for generating Cipher key, Integrity key, Message Authentication Code. Performance analysis evaluates the suitability of LTE Security protocol and LTE network by comparing LTE Security protocol with proposed protocol about algorithm operation count and Latency.Thus, this paper figures out initial identification communication's weak points of currently used LTE security protocol and complements in accordance with traditional protocol. So, it can be applied for traditional LTE communication on account of providing additional confidentiality to initial identifier.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1489-1497
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• 2018

Web application services have diversified. At the same time, research on intrusion detection is continuing due to the surge of cyber threats. Also, As a single-defense system evolves into multi-level security, we are responding to specific intrusions by correlating security events that have become vast. However, it is difficult to check the OS, service, web application type and version of the target system in real time, and intrusion detection events occurring in network-based security devices can not confirm vulnerability of the target system and success of the attack A blind spot can occur for threats that are not analyzed for problems and associativity. In this paper, we propose the validation of effectiveness for intrusion detection events using TF-IDF. The proposed scheme extracts the response traffics by mapping the response of the target system corresponding to the attack. Then, Response traffics are divided into lines and weights each line with an TF-IDF weight. we checked the valid intrusion detection events by sequentially examining the lines with high weights.

• Journal of the Korean Society of Earth Science Education
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• v.13 no.3
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• pp.330-343
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• 2020

In this study, STEAM program on the subject of 'atmospheric circulation and surface current' was produced based on data and applied to 106 first-year high school students to analyze its effect and problem-solving processes. This program was organized to collect, refine, visualize, and analyze data and to allow communication processes to proceed based on these results. Using this, the concept of circulation in daily life was expanded from a global perspective to identify problems about circulation around the world. As a result of the application of the program, significant changes were identified in knowledge information processing competency. Also, significant changes were made in terms of convergence and creativity, which are sub categories among STEAM core competencies. It also sought to obtain suggestions for data-based STEAM education by analyzing students' responses in the form of a Text network.

• Smart Media Journal
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• v.10 no.4
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• pp.71-79
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• 2021

One of the social aspects that changes as the use of the Internet becomes widespread is communication in online space. In the past, only one-on-one conversations were possible remotely, except when they were physically in the same space, but nowadays, technology has been developed to enable communication with a large number of people remotely through bulletin boards, communities, and social network services. Due to the development of such information and communication networks, life becomes more convenient, and at the same time, the damage caused by rapid information exchange is also constantly increasing. Recently, cyber crimes such as sending sexual messages or personal attacks to certain people with recognition on the Internet, such as not only entertainers but also influencers, have occurred, and some of those exposed to these cybercrime have committed suicide. In this paper, in order to reduce the damage caused by malicious comments, research a method for improving the performance of discriminate malicious comments through feature extraction based on parts-of-speech.

• Smart Media Journal
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• v.10 no.4
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• pp.102-110
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• 2021

Currently, the advanced construction technology endorsement system is being operated to promote the development of domestic construction technology. We tried to examine the implicit meanings inherent in advanced construction technologies by analyzing the relationship between emerging vocabularies with high importance in relation to the advanced construction technologies endorsed through this system. For this purpose, 918 cases of advanced construction technology information were collected. Based on the endorsed year and summary of the advanced construction technologies, the importance of the emerging vocabularies was measured for each advanced construction technology. And, based on the LDA model, the degree of influence between related vocabularies was evaluated for each of the four topic areas. Topics according to the technical application fields were analyzed. From 1990 to 2021, the trend of changes in highly influential vocabularies by each topic was inferred. In the future, changes in the degree of influence of the topics of environment, machinery, facilities, and maintenance and reinforcement of structures and related technology fields were predicted.

• Design Convergence Study
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• v.15 no.1
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• pp.233-246
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• 2016

Mobile health industry has been combined with IT technology and is attracting attention. The health application has been developed to provide users a healthy life style. First of all, 5 mobile health applications were selected and reviewed in terms of their service trend. It turned out that none of those applications had any emotional data but physical one. Secondly, to extract users' emotion, technological researches were sorted into different categories. And the result implied that text-based emotion recognition technology is the most suitable for the mobile health service. To implement the service, the application was designed and developed the process of emotion recognition system based on the contents of the research. One-dimension emotion model, which is the standard of classifying emotional data and social network service, was set up as a source. In last, to suggest the usage of health application has been combined with persuasive technology. As a result, this paper prospered a overall service process, concrete service scheme and a guidelines containing 15 services in accordance with the five emotions and time. It is expected to become a direction for indicators considering a psychological individual context.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.2
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• pp.95-115
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• 2023

This study designed a data model linked to Wikidata and examined its applicability to increase the utilization of the digital archive records of the National Debt Redemption Movement, registered as World Memory Heritage, and implications were derived by analyzing the existing metadata, thesaurus, and semantic network graph. Through analysis of the original text of the National Debt Redemption Movement records, key data model classes for linking with Wikidata, such as record item, agent, time, place, and event, were derived. In addition, by identifying core properties for linking between classes and applying the designed data model to actual records, the possibility of acquiring abundant related information was confirmed through movement between classes centered on properties. Thus, this study's result showed that Wikidata's strengths could be utilized to increase data usage in local archives where the scale and management of data are relatively small. Therefore, it can be considered for application in a small-scale archive similar to the National Debt Redemption Movement digital archive.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.232-234
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• 2022

Big data is widely used in customer relationship management, relationship marketing, financial business improvement, credit information and risk management. Moreover, as non-face-to-face financial transactions have become more active recently due to the COVID-19 virus, the use of financial big data is more demanded in terms of relationships with customers. In terms of customer relationship, financial big data has arrived at a time that requires an emotional rather than a technical approach. In relational marketing, it was necessary to emphasize the emotional aspect rather than the cognitive, rational, and rational aspects. Existing traditional financial data was collected and utilized through text-type customer transaction data, corporate financial information, and questionnaires. In this study, the customer's emotional image data, that is, atypical data based on the customer's cultural and leisure activities, is acquired through SNS and the customer's activity image is analyzed with an artificial intelligence CNN algorithm. Activity analysis is again applied to the annotated AI, and the AI big data model is designed to analyze the behavior model shown in the annotation.

• Convergence Security Journal
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• v.23 no.4
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• pp.61-70
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• 2023

Clustering is an unsupervised learning method that involves grouping data based on features such as distance metrics, using data without known labels or ground truth values. This method has the advantage of being applicable to various types of data, including images, text, and audio, without the need for labeling. Traditional clustering techniques involve applying dimensionality reduction methods or extracting specific features to perform clustering. However, with the advancement of deep learning models, research on deep clustering techniques using techniques such as autoencoders and generative adversarial networks, which represent input data as latent vectors, has emerged. In this study, we propose a deep clustering technique based on deep learning. In this approach, we use an autoencoder to transform the input data into latent vectors, and then construct a vector space according to the cluster structure and perform k-means clustering. We conducted experiments using the MNIST and Fashion-MNIST datasets in the PyTorch machine learning library as the experimental environment. The model used is a convolutional neural network-based autoencoder model. The experimental results show an accuracy of 89.42% for MNIST and 56.64% for Fashion-MNIST when k is set to 10.

• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.556-576
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• 2023

This study attempted to find a way to utilize idle spaces in rural areas as a way to respond to rural extinction. Based on the keywords "startup," "youth start-up," and "youth start-up+rural," start-up+rural," the study sought to identify the perception of idle facilities in rural areas through the keywords "Idle facilities" and "closed schools." The study presented basic data for policy direction and plan search by reviewing frequency analysis, major keyword analysis, network analysis, emotional analysis, and domestic and foreign cases. As a result of the analysis, first, it was found that idle facilities and school closures are acting importantly as factors for regional regeneration. Second, in the case of youth startups in rural areas, it was found that not only education on agriculture but also problems for residence should be solved together. Third, in the case of young people, it was confirmed that it was necessary to establish digital utilization for agriculture by actively starting a business using digital. Finally, in order to attract young people and revitalize the region through best practices at home and abroad, policy measures that can serve as various platforms such as culture and education as well as startups should be presented in connection with local residents. These results are significant in that they presented implications for youth start-ups in rural areas by reviewing start-up recognition for the influx of young people as one of the alternatives for the use of idle facilities and regional regeneration, and if additional solutions are presented through field surveys, they can be used to set policy goals that fit the reality.