• The Journal of Korean Association of Computer Education
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• v.22 no.3
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• pp.55-65
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• 2019

In programming language learning system of flip learning methods, the evaluation of cyber lectures generally proceeds from online to multiple choice questions. In this case, the questions are randomly extracted from the question bank and given to individual learners. In order for these evaluation results to be reflected in the grades, the equity of the examination question is more important than anything else. Especially in the programming language subject, the degree of difficulty that learners think can be different depending on the type of problem. In this paper, we classify the types of multiple-choice problems into two categories, and manage the difficulty level by each type. And we propose a question selection algorithm that considers both difficulty level and type of question. Considering the characteristics of the programming language, experimental results show that the proposed algorithm is more efficient and fair than the conventional method.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.587-593
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• 2021

In this thesis, we will break away from the classic DDoS response system for large-scale denial-of-service attacks that develop day by day, and effectively endure intelligent denial-of-service attacks by utilizing artificial intelligence-based technology, one of the core technologies of the 4th revolution. A possible service model development plan was proposed. That is, a method to detect denial of service attacks and minimize damage through machine learning artificial intelligence learning targeting a large amount of data collected from multiple security devices and web servers was proposed. In particular, the development of a model for using artificial intelligence technology is to detect a Western service attack by focusing on the fact that when a service denial attack occurs while repeating a certain traffic change and transmitting data in a stable flow, a different pattern of data flow is shown. Artificial intelligence technology was used. When a denial of service attack occurs, a deviation between the probability-based actual traffic and the predicted value occurs, so it is possible to respond by judging as aggressiveness data. In this paper, a service denial attack detection model was explained by analyzing data based on logs generated from security equipment or servers.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.4
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• pp.629-635
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• 2022

Cyber threats are also increasing with recent social changes and the development of ICT technology. Malicious codes used in cyber threats are becoming more advanced and intelligent, such as analysis environment avoidance technology, concealment, and fileless distribution, to make analysis difficult. Machine learning technology is being used to effectively analyze these malicious codes, but a lot of effort is needed to increase the accuracy of classification. In this paper, we propose a malicious code detection technology based on API call interval characteristics to improve the classification performance of machine learning. The proposed technology uses API call characteristics for each section and entropy of binary to separate characteristic factors into sections based on the extraction malicious code and API call order of normal binary. It was verified that malicious code can be well analyzed using the support vector machine (SVM) algorithm for the extracted characteristic factors.

• The Journal of Korean Institute for Practical Engineering Education
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• v.2 no.1
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• pp.1-7
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• 2010

Recently, interest in u-learning to pursue effective learning by using ubiquitous environment in teaching and learning activities. In u-learning environment, learners should be able to push necessary information at the right time and the right place. Also calm technology oriented to, and this means that it can recognize learners' terminal information and to provide adaptive interface. In u-learning environment, main learning terminals would be mobile terminals which support mobility. However, learning in the existing PC environment should not be excluded. Thus, by providing adaptive interface according to various learners' terminal in LMS for u-learning, learners are able to learn through consistent and natural learning interface with any computer or any network at any place and at any time. The purpose of this study is to propose the interface adaptation based on terminal information focusing on the layout transformation process in the development environment.

• Journal of Digital Convergence
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• v.19 no.1
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• pp.1-10
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• 2021

The purpose of the study is to investigate the impact and analyze the effect of smart learning based class to on the students with low academic achievement level. The study performed in G University in 2018 among students taking calculus II class. It includes 16 students with low academic achievement level, whose grades were under C in the previous calculus I class. They belonged to special class consisted of very low academic achievement level and had to pass calculus II. 3D and AR were actively used in the class. The result shows that they got visual understanding of space, which revealed through analyzing SNS, mid-term and final examination, lecture evaluation. Also, smart learning based mathematics class utilizing smartphone's application elevated academic achievement level and influenced positively on the interest and attitude toward mathematics regardless of previous academic achievement level.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.449-451
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• 2021

Cyber-attacks targeting endpoints have developed sophisticatedly into targeted and intelligent attacks, Advanced Persistent Threat (APT) targeting the Industrial Internet of Things (IIoT) has increased accordingly. Machine learning-based Endpoint Detection and Response (EDR) solutions combine and complement rule-based conventional security tools to effectively defend against APT attacks are gaining attention. However, universal EDR solutions have a high false positive rate, and needs high-level analysts to monitor and analyze a tremendous amount of alerts. Therefore, the process of optimizing machine learning-based EDR solutions that consider the characteristics and vulnerabilities of IIoT environment is essential. In this study, we analyze the flow and impact of IIoT targeted APT cases and compare the method of machine learning-based APT detection EDR solutions.

• Journal of Software Assessment and Valuation
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• v.15 no.2
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• pp.43-50
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• 2019

With the development of IT technology, computer-related crimes are rapidly increasing, and in recent years, the damage to ransomware infections is increasing rapidly at home and abroad. Conventional security solutions are not sufficient to prevent ransomware infections, and to prevent threats such as malware and ransomware that are evolving, a combination of deep learning technologies is needed to detect abnormal behavior and abnormal symptoms. In this paper, a method is proposed to detect user abnormal behavior using CNN-LSTM model and various deep learning models. Among the proposed models, CNN-LSTM model detects user abnormal behavior with 99% accuracy.

• Journal of Science Education
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• v.33 no.1
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• pp.87-99
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• 2009

The purpose of this study was to evaluate the quality of biology contents of cyber home learning systems which provided by 16 metropolitan and provincial offices of education. The contents were evaluated by the 9 categories: needs assessment, instruction design, learning contents, teaching & learning strategy, interaction, supporting system, evaluation, ethicality and copy right. The result showed that the contents have advantage in detailed learning goal, useful learning environment, learning activities by level, and various learning parts material, but lack in evaluation method tool for personal learning by level and the latest learning material. Based on this results, it is expected that the barrier of the efficient learning contents should be searched for the complement, as well as the development high-quality educational contents and the management of cyber home learning system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.441-444
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• 2016

Peace on the Korean Peninsula is threatened by physical aggressions and cyber terrors such as nuclear tests, missile launchings, senior government officials' smart phone hackings and DDos attacks to banking systems. Cyber attacks such as vulnerability for the hackings, malware distributions are generally defended by passive defense through the detecting signs of first invasion and attack, data analysis, adding library and updating vaccine programs. In this paper the concept of security program based on Google TensorFlow machine learning ability to perform adding libraries and solving security vulnerabilities by itself is researched and proposed.

• Journal of The Korean Association of Information Education
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• v.11 no.3
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• pp.339-347
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• 2007

Along with developments of information and communication technologies, internet has spread not only all over the society, but also our everyday life deeply. Recently, requirements for e-learning using internet in the educational aspect have a great influence on the changes of school educations. Cyber Home Learning System, in particular, has been implemented throughout the nation for the purpose of reducing private expenditure for education and promoting substantial improvements in quality of public education. However, there have been exposed many problems with respect to quality of operations and managements of the system comparing to its quantitative growth, and so, at this point in time, researcher conducted analysis of actuality of perceptions of both elementary and middle school teachers with a focus on the case of S System in K province. To test this, total 278 participants were sampled from the elementary schools (139 teachers) and the middle schools (139 teachers) located in K province and were asked to complete a survey and the results therefrom were analyzed accordingly. Results from the analyses revealed that elementary school teachers responded more positively than other respondents in the most areas, including supply of a variety of learning contents of S System, quality of contents, and providing for helps insomuch as to complement school works, etcetera. In addition, researcher has found out that, to make the system become all the more efficient, it shall be required to establish a strategy in order to induce students' interest in the system, as well as to construct infrastructure for facilitating the use of computer. And that there are also needs for continuous supports from both the school and the education authority concerned, and for method of flexible operation of curriculum.