• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.718-721
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• 2012

PMIPv6 (Proxy Mobile IPv6)는 네트워크 기반 이동성 지원 프로토콜로 MN (Mobile Node)의 이동성 프로토콜 스택 유무와 관계없이 MN의 이동성을 지원한다. 하지만 핸드오버 과정에서 이동성 관련 시그널링을 완료할 때까지 지연이 발생하고 핸드오버 동안 MN으로 향하는 패킷이 손실된다는 단점을 갖고 있다. 이러한 단점을 보완하기 위한 기법으로 FPMIPv6 (Fast Handover for PMIPv6)가 제안되었다. 본 논문에서는 PMIPv6의 오픈소스인 OAI PMIPv6 (OpenAirInterface PMIPv6)를 기반으로 FPMIPv6 테스트베드를 구축하고 MN의 핸드오버를 실험하여 실제 FPMIPv6 환경에서의 핸드오버 지연 및 패킷 손실 정도를 측정한다.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.561-570
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• 2015

Till now, applications of many kinds of satellite images have been accentuated in the datacentric scientific studies, researches regarding system development and concerned technologies for them are on the un-matured stage. Especially, satellite image processing requires large volume data handling and specific analysis functionalities, so that practical necessity of base study for system development is emphasized on. In the view of information system, various edged trends such as web standards, cloud computing, or web framework are utilized owing to their application benefits proven and business needs. Considered these aspects, a testing implementation was carried out using OpenStack cloud computing environment and e-government framework. As for the processing functions, WPS in GeoServer, as one of OGC web standards, was applied to perform interoperable data processing scheme between two or more remote servers. Working with the server implemented, client-side was also developed using several open sources such as HTML 5, jQuery, and OpenLayers. If it is that completed further experiments onsite applications with actual multi-data sets and extension of on-demand functionalities with the result of this study, it will be referred as an example case model for complicated and complex system design and implementation which needs cloud computing, geo-spatial web standards and web framework.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.9
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• pp.297-306
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• 2015

Cloud computing has been increasingly used in various fields due to its flexibility, scalability, cost effectiveness, etc. Recently, many scientific communities have been attempting to use cloud computing as a way to deal with difficulties in constructing and operating a research infrastructure. Especially, since they need various collaborations based on networking, such as sharing experimental data, redistributing experimental results, and so forth, cloud computing environment that supports high performance networking is required for scientific communities. To address these issues, we propose RealLab, a high performance cloud platform for collaborative research that provides virtual experimental research environment and data sharing infrastructure over KREONET/GLORIAD. Additionally, we describe some RealLab use cases for showing the swift creation of experimental environment and explain how massive experimental data can be transferred and shared among the community members.

• Journal of Digital Contents Society
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• v.15 no.3
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• pp.395-403
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• 2014

Recently webhard services in various applications have been notably increased. In order to adopt some webhard functions into the existing application platform, however, a lot of manpower and cost is necessary. In this paper, we propose webhard API based on cloud storage for building and extending the webhard functions. The proposed system consists of three layers: application, web-hard server, and storage server in which each layer provides its API independently. It is enable the developer to easily extend the webhard functions to the application by using only HTTP request, which provides no limitation of the programming language. Because our webhard API is running on the virtualized cloud storage, it is possible to easily extend the storages and to reduce the maintenance cost. In this paper, we implement all the webhard API and then show the result of adopting the API to a prototype groupware system.

• Convergence Security Journal
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• v.22 no.3
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• pp.13-18
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• 2022

With the rapid development of IT technology, integration with existing industries has led to an increase in smart manufacturing that simplifies processes and increases productivity based on 4th industrial revolution technology. Security threats are also increasing and there are. In the case of supply chain attacks, it is difficult to detect them in advance and the scale of the damage is extremely large, so they have emerged as next-generation security threats, and research into detection technology is necessary. Therefore, in this paper, we collect, store, analyze, and visualize logs in multiple environments in real time using ELK Stack and Sysmon, which are open source-based analysis solutions, to derive information such as abnormal behavior related to supply chain attacks, and efficiently We try to provide an effective detection method.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.617-627
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• 2016

Many kinds of OGC-based web standards have been utilized in the lots of geo-spatial application fields for sharing and interoperable processing of large volume of data sets containing satellite images. As well, the number of cloud-based application services by on-demand processing of virtual machines is increasing. However, remote sensing applications using these two huge trends are globally on the initial stage. This study presents a practical linkage case with both aspects of OGC-based standard and cloud computing. Performance test is performed with the implementation result for cloud detection processing. Test objects are WPS 2.0 and two types of geo-based service environment such as web server in a single core and multiple virtual servers implemented on OpenStack cloud computing environment. Performance test unit by JMeter is five requests of GetCapabilities, DescribeProcess, Execute, GetStatus, GetResult in WPS 2.0. As the results, the performance measurement time in a cloud-based environment is faster than that of single server. It is expected that expansion of processing algorithms by WPS 2.0 and virtual processing is possible to target-oriented applications in the practical level.

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.11-20
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• 2017

Recently, developments in the various fields of cloud computing technology has been utilized. Whereas the demand for cloud computing services is increasing, security threats are also increasing in the cloud computing environments. Especially, in case when the hosts interconnected in the cloud environments are infected and propagated through the attacks by malware. It can have an effect on the resource of other hosts and other security threats such as personal information can be spreaded and data deletion. Therefore, the study of malware analysis to respond these security threats has been proceeded actively. This paper proposes a type of attack clustering method of Zeus botnet using the k-means clustering algorithm for malware analysis that occurs in the cloud environments. By clustering the malicious activity by a type of the Zeus botnet occurred in the cloud environments. it is possible to determine whether it is a malware or not. In the future, it sets a goal of responding to an attack of the new type of Zeus botnet that may occur in the cloud environments.

• Korean Journal of Environmental Agriculture
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• v.37 no.4
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• pp.251-259
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• 2018

BACKGROUND: Various culture media have been used for hydroponic cultures of horticultural plants under the smart greenhouses with natural and artificial light types. Management of the culture medium for the control of medium amounts and/or necessary components absorbed by plants during the cultivation period is performed with ICT (Information and Communication Technology) and/or IoT (Internet of Things) in a smart farm system. This study was conducted to develop the cloud-based data analysis system for effective management of culture medium applying to hydroponic culture and plant growth in smart greenhouses. METHODS AND RESULTS: Conventional inorganic Yamazaki and organic media derived from agricultural byproducts such as a immature fruit, leaf, or stem were used for hydroponic culture media. Component changes of the solutions according to the growth stage were monitored and plant growth was observed. Red and green lettuce seedlings (Lactuca sativa L.) which developed 2~3 true leaves were considered as plant materials. The seedlings were hydroponically grown in the smart greenhouse with fluorescent and light-emitting diodes (LEDs) lights of $150{\mu}mol/m^2/s$ light intensity for 35 days. Growth data of the seedlings were classified and stored to develop the relational database in the virtual machine which was generated from an open stack cloud system on the base of growth parameter. Relation of the plant growth and nutrient absorption pattern of 9 inorganic components inside the media during the cultivation period was investigated. The stored data associated with component changes and growth parameters were visualized on the web through the web framework and Node JS. CONCLUSION: Time-series changes of inorganic components in the culture media were observed. The increases of the unfolded leaves or fresh weight of the seedlings were mainly dependent on the macroelements such as a $NO_3-N$, and affected by the different inorganic and organic media. Though the data analysis system was developed, actual measurement data were offered by using the user smart device, and analysis and comparison of the data were visualized graphically in time series based on the cloud database. Agricultural management in data visualization and/or plant growth can be implemented by the data analysis system under whole agricultural sites regardless of various culture environmental changes.