• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.189-206
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• 2005

Much of work on network externality assumed network effects are dependent on the network size. Therefore, very little consideration is given to the view that marginal benefits from joining the network may not increase with the network size if consumer benefits come from the direct interaction with neighbors, namely local network. In this study, we used the agent-based simulation method to reexamine the effectiveness of the traditional network market strategy under the presence of the local network where two incompatible technologies compete. We found that the strategy of growing an initial customer base is not effective under the presence of the local network. Our study also showed that targeting customers based on their technology Preference is not as effective as targeting customers within the same local network. As a result, the focus of a network market strategy should be directed to taking advantage of the customer network.

• KNOM Review
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• v.21 no.2
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• pp.1-9
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• 2018

Network virtualization refers to a technology creating independent virtual network environment on a physical network. Network virtualization technology can share the physical network resources to reduce the cost of establishing the network for each user and enables the network administrator to dynamically change the network configuration according to the purpose. Although the network management can be handled dynamically, the management is manual, and it does not maximize the profit of network virtualization. In this paper, we propose Machine-Learning technology to allow the network to learn by itself and manage its management dynamically. The proposed approach is to dynamically allocate appropriate resources by predicting resource demand of VNF in service function chaining, which is a core and essential problem in virtual network management. Our goal is to predict the resource demand of the VNF and dynamically allocate the appropriate resources to reduce the cost of network operation while preventing service interruption.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.23-30
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• 2022

Glaucoma is a chronic neuropathy that affects the optic nerve which can lead to blindness. The detection and prediction of glaucoma become possible using deep neural networks. However, the detection performance relies on the availability of a large number of data. Therefore, we propose different frameworks, including a hybrid of a generative adversarial network and a convolutional neural network to automate and increase the performance of glaucoma detection. The proposed frameworks are evaluated using five public glaucoma datasets. The framework which uses a Deconvolutional Generative Adversarial Network (DCGAN) and a DenseNet pre-trained model achieves 99.6%, 99.08%, 99.4%, 98.69%, and 92.95% of classification accuracy on RIMONE, Drishti-GS, ACRIMA, ORIGA-light, and HRF datasets respectively. Based on the experimental results and evaluation, the proposed framework closely competes with the state-of-the-art methods using the five public glaucoma datasets without requiring any manually preprocessing step.

• Bulletin of the Korean Space Science Society
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• 2009.04a
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• pp.56.2-56.2
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• 2009

• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.157-163
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• 2009

With the wide usage of internet in many fields, networks are being exposed to many security threats, such as DDoS attack and worm/virus. For enterprise network, prevention failure of network security causes the revealing of commercial information or interruption of network services. In this paper, we propose a method of prevention of DDoS attacks for enterprise network based on traceback and network traffic analysis. The model of traceback implements the detection of IP spoofing attacks by the cooperation of trusted adjacent host, and the method of network traffic analysis implements the detection of DDoS attacks by analyzing the traffic characteristic. Moreover, we present the result of the experiments, and compare the method with other methods. The result demonstrates that the method can effectively detect and block DDoS attacks and IP spoofing attacks.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.219-230
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• 2023

Wireless Body Area Networks (WBANs) have made it easier for healthcare workers and patients to monitor patients' status continuously in real time. WBANs have complex and diverse network structures; thus, management and control can be challenging. Therefore, considering emerging Software-defined networks (SDN) with WBANs is a promising technology since SDN implements a new network management and design approach. The SDN concept is used in this study to create more adaptable and dynamic network architectures for WBANs. The study focuses on comparing the performance of two SDN controllers, POX and Ryu, using Mininet, an open-source simulation tool, to construct network topologies. The performance of the controllers is evaluated based on bandwidth, throughput, and round-trip time metrics for networks using an OpenFlow switch with sixteen nodes and a controller for each topology. The study finds that the choice of network controller can significantly impact network performance and suggests that monitoring network performance indicators is crucial for optimizing network performance. The project provides valuable insights into the performance of SDN-based WBANs using POX and Ryu controllers and highlights the importance of selecting the appropriate network controller for a given network architecture.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.801-817
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• 2021

Network virtualization technologies have played efficient roles in deploying cloud, Internet of Things (IoT), big data, and 5G network. We have conducted a survey on network virtualization technologies, such as software-defined networking (SDN), network functions virtualization (NFV), and network virtualization overlay (NVO). For each of technologies, we have explained the comprehensive architectures, applied technologies, and the advantages and disadvantages. Furthermore, this paper has provided a summarized view of the latest research works on challenges and solutions of security issues mainly focused on DDoS attack and encryption.

• Proceedings of the Korean Magnetic Resonance Society Conference
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• 2002.01a
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• pp.25-25
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• 2002

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.303-309
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• 2022

Software Defined Networking (SDN) is a novel approach that have accelerated the development of numerous technologies such as policy-based access control, network virtualization, and others. It allows to boost network architectural flexibility and expedite the return on investment. However, this increases the system's complexity, necessitating the expenditure of dollars to assure the system's security. Network Function Virtualization (NFV) opens up new possibilities for network engineers, but it also raises security concerns. A number of Internet service providers and network equipment manufacturers are grappling with the difficulty of developing and characterizing NFVs and related technologies. Through Moodle's efforts to maintain security, this paper presents a detailed review of security-related challenges in software-defined networks and network virtualization services.

• 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.