• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.201-209
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• 2021

The term, eGovernmen or e-Government, uses technology communications devices such as computers and the Internet to provide public services to citizens and others. The eGovernment or e-government provides citizens with new opportunities to access the government directly and conveniently, while the government provides citizens with directservices. Also, in these days, cloud computing is a feature that enables users to use computer system resources, especially data storage (cloud storage) and on-demand computing power, without having to manage themselves. The term is commonly used to describe data centers that are available to many users over the Internet. Today, the dominant Big Cloud is distributed across multiple central servers. You can designate it as an Edge server if it is relatively close to the user. However, despite the prevalence of e-government and cloud computing, each of these concepts has evolved. Research attempts to combine these two concepts were not being made properly. For this reason, in this work, we aim to produce independent and objective analysis results by separating progress steps for the analysis of e-government cloud service platforms. This work will be done through an analysis of the development process and architectural composition of the e-government development standard framework and the cloud platform PaaS-TA. In addition, this study is expected to derive implications from an analysis perspective on the direction and service composition of the e-government cloud service platform currently being pursued.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1014-1025
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• 2020

Cloud computing services changed the way the data are managed across the healthcare system that can improve patient care. Currently, most healthcare organizations are using cloud-based applications and related services to deliver better healthcare facilities. But architecting a cloud-based healthcare system needs deep knowledge about the working nature of these services and the requirements of the healthcare environment. The success is based on the usage of appropriate cloud services in the architecture to manage the data flow across the healthcare system.Cloud service providers offer a wide variety of services to ingest, store and process healthcare data securely. The top three public cloud providers- Amazon, Google, and Microsoft offers advanced cloud services for the solution that the healthcare industry is looking for. This article proposes a framework that can effectively utilize cloud services to handle the data flow among the various stages of the healthcare infrastructure. The useful cloud services for ingesting, storing and analyzing the healthcare data for the proposed framework, from the top three cloud providers are listed in this work. Finally, a cloud-based healthcare architecture using Amazon Cloud Services is constructed for reference.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1286-1306
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• 2022

Searchable symmetric encryption (SSE) provides a safe and effective solution for retrieving encrypted data on cloud servers. However, the existing SSE schemes mainly focus on single keyword search in single client, which is inefficient for multiple keywords and cannot meet the needs for multiple clients. Considering the above drawbacks, we propose a scheme enabling dynamic multi-client and Boolean query in searchable symmetric encryption for cloud storage system (DMC-SSE). DMC-SSE realizes the fine-grained access control of multi-client in SSE by attribute-based encryption (ABE) and novel access control list (ACL), and supports Boolean query of multiple keywords. In addition, DMC-SSE realizes the full dynamic update of client and file. Compared with the existing multi-client schemes, our scheme has the following advantages: 1) Dynamic. DMC-SSE not only supports the dynamic addition or deletion of multiple clients, but also realizes the dynamic update of files. 2) Non-interactivity. After being authorized, the client can query keywords without the help of the data owner and the data owner can dynamically update client's permissions without requiring the client to stay online. At last, the security analysis and experiments results demonstrate that our scheme is safe and efficient.

• KIISE Transactions on Computing Practices
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• v.21 no.7
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• pp.470-475
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• 2015

Openstack is an open source software that enables developers to build IaaS(Infrastructure as a Service) cloud platforms. Openstack can virtualize servers, networks and storages, and provide them to users. This paper proposes the structure of Openstack cloud storage system applying Infiniband to solve bottlenecking that may occur between server and storage nodes when the server performs an I/O operation. Furthermore, we implement all flash array based high-performance Cinder storage volumes which can be used at Nova virtual machines by applying distributed RAID-60 structures to three 8-bay SSD storages and show that Infiniband storage networks applied to Openstack is suitable for virtualizing high-performance storage.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.179-186
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• 2017

Managing students' data is a high prioritized duty of the university administration since most of the school affairs are proceed based on that database. Universities have invested in IT assets such as servers, storage, database, and networks. However, continuing investment in IT infrastructure is impossible due to limited budget and rapid changes in the educational environment. As cloud computing diffuse, universities are trying to reduce costs and improve efficiency by increasing server utilization, unlike when physically investing. We designed a hypothetical academic information management system based on cloud computing by utilizing the advanced server virtualization technology. This administrative cloud system allows universities to improve the availability of the system with low cost. The system demonstrates its flexibility of using data resources and immediacy of resumption.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.3
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• pp.59-68
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• 2012

Zero client-based cloud storage technology is gaining much interest as a tool to centralized management of organizational documents nowadays. Besides the well-known cloud storage's defects such as security and privacy protection, users of the zero client-based cloud storage point out the difficulty in browsing and selecting the storage category because of its diversity and complexity. To resolve this problem, this study proposes a method of intelligent document archiving by applying an algorithm-based automatic topic identification technology. Without user's direct definition of category to store the working document, the proposed methodology and prototype enable the working documents to be automatically archived into the predefined categories according to the extracted topic. Based on the proposed ideas, more effective and efficient centralized management of electronic documents can be achieved.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.45-52
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• 2014

The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.

• Journal of Korea Entertainment Industry Association
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• v.5 no.1
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• pp.149-153
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• 2011

In this study, a configuration method for a cloud technology based VoD system through two different scenarios is proposed. The first scenario virtualizes DMC, content storages for each SO, and stream servers in the conventional VoD system in order to efficiently use the additionally required storage capacity and stream server. In the second scenario, it is proposed that cable broadcasting systems including VoD systems are to be changed as cloud in which the subscriber STB should have minimum programs and storage regions to connect networks, and the operating system and middle ware presented in the existing subscriber STB is moved to the cloud data center. In addition, the comparison of the application of the cloud technology for the cost of changing the existing system to STB and the cost of establishing a cloud VoD system is performed in order to analyze the cost reduction in broadcasting businesses based on the establishment of VoD systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2703-2718
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• 2015

Nowadays, public cloud storage is gaining popularity and a growing number of users are beginning to use the public cloud storage for online data storing and sharing. However, how the encrypted data stored in public clouds can be effectively shared becomes a new challenge. Proxy re-encryption is a public-key primitive that can delegate the decryption right from one user to another. In a proxy re-encryption system, a semi-trusted proxy authorized by a data owner is allowed to transform an encrypted data under the data owner's public key into a re-encrypted data under an authorized recipient's public key without seeing the underlying plaintext. Hence, the paradigm of proxy re-encryption provides a promising solution to effectively share encrypted data. In this paper, we propose a new certificate-based proxy re-encryption scheme for encrypted data sharing in public clouds. In the random oracle model, we formally prove that the proposed scheme achieves chosen-ciphertext security. The simulation results show that it is more efficient than the previous certificate-based proxy re-encryption schemes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.435-437
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• 2013

This paper proposes a system composed of wireless sensor network and cloud to monitor storage environment of pharmaceutical products. Integration of sensor networks to cloud is an emerging architecture offering the benefits of internet for monitoring to be done easily and remotely from anywhere and anytime and at the same time freeing the sensor network from processing, analysis, computational and storage of sensor data.