• Journal of Industrial Convergence
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• v.19 no.3
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• pp.27-34
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• 2021

In the era of the 4th industrial revolution, the age of artificial intelligence, the development of ICT technology is having various effects on the online and offline educational environment. The universal access of online education changes the educational paradigm and converts it to a learner-centered service. At the time when a new educational environment is required to change, interest in flip learning is increasing. Even adult learner's online learning needs is also shown very high. The purpose of this study was to investigate how repetitive learning activities through flip learning for middle-aged online learners of K-Cyber University has a relationship and structural relationship between the effects of learning immersion and learning interest on learning satisfaction. Through this study, there is significance in research to suggest direction for learning satisfaction based on flip learning. For further studies, if a model of analysis of various factors that can be measured is specified and applied, it can be used as a research background that can maximize learning satisfaction based on flip learning.

• Digital Contents
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• no.3 s.142
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• pp.108-111
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• 2005

OnExpo는 2,000여개에 이르는 국내 디지털콘텐츠 기업 정보를 온라인상에 연중무휴로 상시 제공하며, 전시 기업들의 국내외 홍보와 마케팅을 지원하는 국내 최대 규모의 디지털콘텐츠 가상 전시장이다. 특히 OnExpo는 3월 새 학기를 맞아, 국내 e러닝 온라인 콘텐츠와 솔루션을 한자리에서 소개하는‘2005 e러닝 OnExpo’를 개최한다.이에 디지털콘텐츠 사이버전시장 OnExpo(www.onexpo.or.kr) 입점을 소개하는‘OnExpo Hot & Cool’을 연재한다. 그 첫 번째로, ‘2005 e러닝 OnExpo’참가 기업 중 업계에서 두각을 나타내고 있는 기업을 탐방해,e러닝 시장의 현황과 사업전략 그리고 앞으로의 계획에 대해 들어봤다.

• Digital Contents
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• no.4 s.143
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• pp.102-106
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• 2005

OnExpo는 2,000여개에 이르는 국내 디지털콘텐츠 기업 정보를 온라인상에 연중무휴로 상시 제공하며,전시 기업들의 국내외 홍보와 마케팅을 지원하는 국내 최대 규모의 디지털콘텐츠 가상 전시장이다. 특히 OnExpo는 3월 새 학기를 맞아, 국내 e러닝 온라인 콘텐츠와 솔루션을 한자리에서 소개하는‘2005 e러닝 OnExpo’를 개최했다. 이에 디지털콘텐츠 사이버전시장 OnExpo(www.onexpo.or.kr) 입점을 소개하는‘OnExpo Hot & Cool’을 연재한다. ‘2005 e러닝 OnExpo’참가 기업 중 업계에서 두각을 나타내고 있는 기업을 탐방해, e러닝 시장의 현황과 사업전략 그리고 앞으로의 계획에 대해 들어봤다.

• Journal of Software Assessment and Valuation
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• v.15 no.2
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• pp.121-128
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• 2019

Computing systems have various vulnerabilities to cyber attacks. In particular, various cyber attacks that are intelligent in the information society have caused serious social problems and economic losses. Traditional security systems are based on misuse-based technology, which requires the continuous updating of new attack patterns and the real-time analysis of vast amounts of data generated by numerous security devices in order to accurately detect. However, traditional security systems are unable to respond through detection and analysis in real time, which can delay the recognition of intrusions and cause a lot of damage. Therefore, there is a need for a new security system that can quickly detect, analyze, and predict the ever-increasing cyber security threats based on machine learning and big data analysis models. In this paper, we present a IDS model that combines machine learning and big data technology.

• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.39-48
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• 2022

Cyberattacks around the world continue to increase, and their damage extends beyond government facilities and affects civilians. These issues emphasized the importance of developing a system that can identify and detect cyber anomalies early. As above, in order to effectively identify cyber anomalies, several studies have been conducted to learn BGP (Border Gateway Protocol) data through a machine learning model and identify them as anomalies. However, BGP data is unbalanced data in which abnormal data is less than normal data. This causes the model to have a learning biased result, reducing the reliability of the result. In addition, there is a limit in that security personnel cannot recognize the cyber situation as a typical result of machine learning in an actual cyber situation. Therefore, in this paper, we investigate BGP (Border Gateway Protocol) that keeps network records around the world and solve the problem of unbalanced data by using SMOTE. After that, assuming a cyber range situation, an autoencoder classifies cyber anomalies and visualizes the classified data. By learning the pattern of normal data, the performance of classifying abnormal data with 92.4% accuracy was derived, and the auxiliary index also showed 90% performance, ensuring reliability of the results. In addition, it is expected to be able to effectively defend against cyber attacks because it is possible to effectively recognize the situation by visualizing the congested cyber space.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.01a
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• pp.73-74
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• 2018

최근 사이버대학들은 치열한 입시경쟁을 겪고 있다. 이에 학교들은 교육질 개선을 위하여 다양한 노력을 하고 있다. S 사이버대학의 경우 최초로 전과목별로 실시간 채팅서비스를 제공하여 동영상 강의와 게시판의 한계를 극복하고자 하고 있다. 본 연구에서는 이러닝 교육의 학습효과를 종속변수로 설정하고, 학습내용, 교수설계요인과 채팅서비스를 독립변수로 투입하여, 다중회귀분석을 기법을 통해 분석하였다. 분석결과 학습내용, 교수설계요인, 채팅서비스 모두는 학습효과에 영향을 미치는 것으로 나타났다. 본 연구에서는 전교과목에 적용한 채팅서비스는 온라인 교육 효과를 높일 수 있는 방안임을 확인하였고, 효과적인 채팅 서비스의 활용방안을 제시하고자 한다.

• Journal of Practical Engineering Education
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• v.10 no.1
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• pp.25-33
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• 2018

As the IT industry develops, The field of e-learning based on existing theoretical subjects has expanded to fields requiring actual education. Courses that require practical training in e-learning must be evaluated to have learning outcomes through on-line practice. In this research, a student at Cyber University mechatronics engineering studies 'PLC Control' and 'Servo Motor Control', which are subjects of the undergraduate major, through 'Prime College's CyberLAB' for learning by e-learning investigated whether there was a learning result. For this reason, CyberLAB was conducted. And for the students who took the course for two years, We confirmed through the 5 - point scale questionnaire and grades that the practical subjects had a significant effect on e - learning.

• Smart Media Journal
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• v.12 no.11
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• pp.36-47
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• 2023

Industrial Control System(ICS), which controls facilities at major industrial sites, is increasingly connected to other systems through networks. With this integration and the development of intelligent attacks that can lead to a single external intrusion as a whole system paralysis, the risk and impact of security on industrial control systems are increasing. As a result, research on how to protect and detect cyber attacks is actively underway, and deep learning models in the form of unsupervised learning have achieved a lot, and many abnormal detection technologies based on deep learning are being introduced. In this study, we emphasize the application of preprocessing methodologies to enhance the anomaly detection performance of deep learning models on time series data. The results demonstrate the effectiveness of a Wavelet Transform (WT)-based noise reduction methodology as a preprocessing technique for deep learning-based anomaly detection. Particularly, by incorporating sensor characteristics through clustering, the differential application of the Dual-Tree Complex Wavelet Transform proves to be the most effective approach in improving the detection performance of cyber attacks.

• The Journal of Korean Association of Computer Education
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• v.16 no.3
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• pp.49-60
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• 2013

This study is aimed to investigate that the blended e-learning could enhance the effectiveness compared to the conventional lecture performed in classroom. At first, both the CbE(Class based E-learning) and the EbC(E-learning based Class) mode have been generated in blended e-learning operation method following the process which analyze the various studies of interest. In addition, the instruction structures of Z Type(Zigzag model) and H-Type(Ladder model) were established as proposed model. The H-Blended e-learning based on CbE mode was introduced in the Excel Spread Sheet subject which held in A University to achieve the goal of this study. Learners were categorized and belonged to either the group 1(over 50% of attendance in cyber lecture) or the group 2(the rest of them). The data analysis was performed with $x^2$-test, t -test to compare the achievement of study between groups. The t -test result showed that the academic achievement in learning with group 1 was statistically significant than the learner in group 2. The effectiveness of the blended e-learning has been proved as the logistic regression analysis showed that the rate of the attendance in the cyber lecture functioned as indicator that enable to predict the acceptance.

• The Journal of Korean Association of Computer Education
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• v.8 no.4
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• pp.25-36
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• 2005

Data of 650 college students in the nation were collected by mail in 2001 Nov. Students preference over cyber communication methods were SMS message, messenger, blog, e-mail in that order. Younger students prefer SMS messages while older students prefer e-mail in relative term. Mobile phone is used more for SMS message than voice communication which is more so with females. The rate of non e-mail use is 57.8%, particularly males(61.9%) and younger students(69.4%) are higher. E-mail, once was very high in use, is being replaced by new media. Suggestion for e-learning environment are being connected, immediacy, active use of blog, more use of fun multimedia information.