• International journal of advanced smart convergence
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• v.8 no.4
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• pp.113-120
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• 2019

Recently, the artificial intelligence(AI) is used in various environments in life, and research on this is being actively conducted in education. In this paper, we designed a Design-Based Research(DBR)-based AI programming education program and analyzed the application of the program for the improvement of understanding of AI in elementary school. In the artificial intelligence education program in elementary school, we should considerthat itshould be used in conjunction with software education through programming activities, rather than creating interest through simple AI experiences. The designed education program reflects the collaborative problem-solving procedures following the DBR process of analysis - design - execution - redesign, allowing the real-world problem-solving activities using AI experiences and block-type programming language. This paper also examined the examples of education programs to improve understanding of AI by using Machine Learning for Kids and to draw implications for developing and operating such a program.

• Convergence Security Journal
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• v.16 no.7
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• pp.3-11
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• 2016

With repid development of optical networking technology, Software-Defined Network (SDN) and Network Function Virtualization (NFV), high performance networking service, collaboration platform that enables collaborative research globally, drastically National Research Network (NRN) including Internet Service has changed. Therefore we compared and analyzed several world-class NRNs and took a view of future development strategy of the NRN. Also we suggest high speed security environment in super high bandwidth network with 40Gbps and 100Gbps optical transmission technology, network separation of NRN with Science DMZ to support high performance network transmission for science big data, building security environment for last-mile in campus network that supports programmability of IDS using BRO framework.

• Convergence Security Journal
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• v.5 no.4
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• pp.33-40
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• 2005

As e-learning studying is activated, learner's requirement increased. Therefore, need correct e-learning model augmented requirement of learner and new ubiquitous surrounding. In this treatise when, proposed to supplement studying contents relationship conversion service and cooperation studying service function to LMS that analyze existing e-learning model's limitation for ubiquitous environment e-learning model that can study regardless of, ubiquitously some contents and do based on SCORM ubiquitous-network and next generation sensor technology etc. Learning form conversion service senses a learner's surrounding situations and recognize his/her body condition using smart sensor technology and provides the learner with contents in the optimal form. Using sensing projects like Orestia and SOB, users can more effective collaborative learning service.

• Convergence Security Journal
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• v.11 no.1
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• pp.57-69
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• 2011

Many heterogeneous Intrusion Detection Systems(IDSs) based in misuse detection technique including the self-developed IDS are now operating in Defense-ESM(Enterprise Security Management System). IDS based on misuse detection may have different capability in the intrusion detection process according to the frequency and quality of its signature update. This makes the integration and collaboration with other IDSs more difficult. In this paper, with the purpose of creating the proper foundation for integration and collaboration between heterogeneous IDSs being operated in Defense-ESM, we propose an effective mechanism that can enable one IDS to propagate its new detection rules to other IDSs and receive updated rules from others. We also prove the performance of rule exchange and application possibility to defense environment through the implementation and experiment.

• Convergence Security Journal
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• v.13 no.4
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• pp.41-46
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• 2013

Routing protocol using in the existing wire network cannot be used as it is for efficient data transmission in MANET. Because it consists of only mobile nodes, network topology is changing dynamically. Therefore, each mobile node must perform router functions. Variety of routing attack like DoS in MANET is present owing to these characteristic. In this paper, we proposed cooperative-based detection method to improve detection performance of flooding attack which paralyzes network by consuming resource. Accurate attack detection is done as per calculated adaptively threshold value considered the amount of all network traffic and the number of nodes. All the mobile nodes used a table called NHT to perform collaborative detection and apply cluster structure to the center surveillance of traffic.

• Journal of Korea Multimedia Society
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• v.21 no.11
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• pp.1297-1304
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• 2018

Online education, commonly referred to as distance education, has developed rapidly. However, it is questionable whether such distance education has been applied to various educational fields and has achieved satisfactory results in terms of learning effect. One of the reasons for not maximizing the benefits of distance education is non-dynamicity in the production and application of educational content. Educational contents production is made up of collaborative work between the instructor who is the contents expert and the developer who is the production expert. For this reason, existing researches have also concentrated on the improvement of each educational effect. In this paper, we propose to replace a production expert from a developer to an instructor. At this time, the important point is that the educational contents produced by the instructor, who is a development non-expert, should still be able to be maintained with high-quality contents utilizing the characteristics of the web. For this purpose, the production system was developed based on open source to maintain the quality similar to the educational contents developed by the production expert. This will increase the effectiveness of education by applying the developed Smart-Blended Learning System to various educational sites.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1687-1707
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• 2022

With the development of multiuser online meetings, more group-oriented technologies and applications for instance collaborative work are becoming increasingly important. Authenticated Group Key Agreement (AGKA) schemes provide a shared group key for users with after their identities are confirmed to guarantee the confidentiality and integrity of group communications. On the basis of the Public Key Cryptography (PKC) system used, AGKA can be classified as Public Key Infrastructure-based, Identity-based, and Certificateless. Because the latter type can solve the certificate management overhead and the key escrow problems of the first two types, Certificateless-AGKA (CL-AGKA) protocols have become a popular area of research. However, most CL-AGKA protocols are vulnerable to Public Key Replacement Attacks (PKRA) due to the lack of public key authentication. In the present work, we present a CL-AGKA scheme that can resist PKRA in order to solve impersonation attacks caused by those attacks. Beyond security, improving scheme efficiency is another direction for AGKA research. To reduce the communication and computation cost, we present a scheme with only one round of information interaction and construct a CL-AGKA scheme replacing the bilinear pairing with elliptic curve cryptography. Therefore, our scheme has good applicability to communication environments with limited bandwidth and computing capabilities.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.924-935
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• 2023

Purpose: The central aim of this study is to leverage machine learning techniques for the classification of Intrusion Detection System (IDS) data, with a specific focus on identifying the variables responsible for enhancing overall performance. Method: First, we classified 'R2L(Remote to Local)' and 'U2R (User to Root)' attacks in the NSL-KDD dataset, which are difficult to detect due to class imbalance, using seven machine learning models, including Logistic Regression (LR) and K-Nearest Neighbor (KNN). Next, we use the SHapley Additive exPlanation (SHAP) for two classification models that showed high performance, Random Forest (RF) and Light Gradient-Boosting Machine (LGBM), to check the importance of variables that affect classification for each model. Result: In the case of RF, the 'service' variable and in the case of LGBM, the 'dst_host_srv_count' variable were confirmed to be the most important variables. These pivotal variables serve as key factors capable of enhancing performance in the context of classification for each respective model. Conclusion: In conclusion, this paper successfully identifies the optimal models, RF and LGBM, for classifying 'R2L' and 'U2R' attacks, while elucidating the crucial variables associated with each selected model.

• Journal of Korean Society of Environmental Engineers
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• v.35 no.8
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• pp.533-539
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• 2013

Korea is one of the top countries that has funded great amount to promote basic research and others in recent decade. While the quantity of R&D fund in Korea has rapidly increased, the effectiveness and quality of R&D outcomes became a controversial issue. National Research Foundation of Korea (NRF) and Korea Environmental Industry & Technology Institute (KEITI) agreed to collaborate for diffusing and utilizing R&D outcomes of each institute. NSF and KEITI signed the bilateral MOU in 2012, and Interministerial Collaborative R&D Support Framework (ICR&DSF) was developed. The ICR&DSF consist of launching an Eco-Bridge Program as an interministerial R&D program and composition of Environmental Convergence R&D Bridge Committee. The Eco-Bridge Program was applied to 'Environmental Convergence Technology Project' of KEITI as a pilot program in 2012. The unique feature of this interministerial R&D program is that the Eco-Bridge Program directly supports the basic research outcomes which are previously funded by NRF. As the collaboration between NRF and KEITI becomes stronger, it is expected to explore the more creative and the more transformative research.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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• pp.328-338
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• 2006

A new evolutionary computation technique, called particle swarm optimization(PSO), has been proposed and introduced recently. PSO has been inspired by the social behavior of flocking organisms, such as swarms of birds and fish schools and PSO is an algorithm that follows a collaborative population-based search model. Each particle of swarm flies around in a multidimensional search space looking for the optimal solution. Then, Particles adjust their position according to their own and their neighboring-particles experience. In this paper, characteristics of PSO such as mentioned are reviewed and compared with GA which is based on the evolutionary mechanism in natural selection. Also dimensionalities of PSO and GA are compared throughout numeric experimental studies. The comparative studies demonstrate that PSO is characterized as simple in concept, easy to implement, and computationally efficient and can generate a high-quality solution and stable convergence characteristic than GA.