• 제목/요약/키워드: cloud model

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A Study on the Secure Cloud Federation Model of Korean Public and Administrative Institutions based on U.S. TIC 3.0 (미국 정부 TIC 3.0을 적용한 국내 공공·행정기관의 안전한 클라우드 연합 모델 연구)

  • Soo-hyun Lee;Ha-neul Lim;Byung-chul Bae;Eunseong Kang;Hyung-Jong Kim
    • Journal of Internet Computing and Services
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    • 제24권6호
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    • pp.13-21
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    • 2023
  • Recently, due to the collapse of boundaries between fields caused by COVID-19, the government's goal of connecting all data and making it accessible to people, businesses, and governments has garnered attention. To achieve this goal, cloud technology is consistently mentioned, and since the use of cloud technology inevitably raises security concerns, various studies are being conducted on the topic. This paper analyzes the use of cloud technology in public and administrative institutions in Korea and presents a model that applies the U.S. government's TIC 3.0 concept to mitigate potential security issues. The objective is to provide a secure cloud service utilization model for public and administrative institutions, with reference to TIC 3.0.

A Study on Service Security Framework for SW-IaaS Cloud (SW-IaaS 클라우드 서비스 보안 프레임워크에 관한 연구 - SW-IaaS를 중심으로)

  • Choi, Myeonggil;Park, Choonsik;Jeong, Jaehun
    • Journal of the Korea Institute of Information Security & Cryptology
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    • 제26권2호
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    • pp.319-325
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    • 2016
  • Cloud computing-related security incidents have occurred recently are beyond the scope of a enterprise's security incident is expanded to the entire range of customers who use the cloud computing environment. The control technology for the overall integrated security of the cloud data center is required for this purpose. This study research integrated and additional security elements for the cloud data center control to understand the existing control technology. It is a better understanding of the IaaS cloud environment to build the IaaS cloud environment by CloudStack. SW-IaaS cloud structure by combining CloudStack and IaaS cloud model presented by NIST is proposed in this study. This paper derive a security framework to consider in each layer of The SW-IaaS cloud components, which are composed of the Cloud Manager, Cluster Manager, and Computer Manager.

Optimization of Energy Consumption in the Mobile Cloud Systems

  • Su, Pan;Shengping, Wang;Weiwei, Zhou;Shengmei, Liu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권9호
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    • pp.4044-4062
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    • 2016
  • We investigate the optimization of energy consumption in Mobile Cloud environment in this paper. In order to optimize the energy consumed by the CPUs in mobile devices, we put forward using the asymptotic time complexity (ATC) method to distinguish the computational complexities of the applications when they are executed in mobile devices. We propose a multi-scale scheme to quantize the channel gain and provide an improved dynamic transmission scheduling algorithm when offloading the applications to the cloud center, which has been proved to be helpful for reducing the mobile devices energy consumption. We give the energy estimation methods in both mobile execution model and cloud execution model. The numerical results suggest that energy consumed by the mobile devices can be remarkably saved with our proposed multi-scale scheme. Moreover, the results can be used as a guideline for the mobile devices to choose whether executing the application locally or offloading it to the cloud center.

TEST ON REAL-TIME CLOUD DETECTION ALGORITHM USING A NEURAL NETWORK MODEL FOR COMS

  • Ahn, Hyun-Jeong;Chung, Chu-Yong;Ou, Mi-Lim
    • Proceedings of the KSRS Conference
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    • 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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    • pp.286-289
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    • 2007
  • This study is to develop a cloud detection algorit1un for COMS and it is currently tested by using MODIS level 2B and MTSAT-1R satellite radiance data. Unlike many existing cloud detection schemes which use a threshold method and traditional statistical methods, in this study a feed-forward neural network method with back-propagation algorit1un is used. MODIS level 2B products are matched with feature information of five-band MTSAT 1R image data to form the training dataset. The neural network is trained over the global region for the period of January to December in 2006 with 5 km spatial resolution. The main results show that this model is capable to detect complex cloud phenomena. And when it is applied to seasonal images, it shows reliable results to reflect seasonal characteristics except for snow cover of winter. The cloud detection by the neural network method shows 90% accuracy compared to the MODIS products.

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A Study on Design and Application of Central Archives Management System Based on Cloud Computing (클라우드 컴퓨팅 기반 중앙기록물관리시스템 설계 및 적용에 관한 연구)

  • Jung, Yeyong;Shim, Gab-Yong;Kim, Yong
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • 제25권4호
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    • pp.209-233
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    • 2014
  • This study is to propose an archive management model based on cloud computing for preservation and utilization, as analyzing the characteristic of business model, electronic records and archival system. To achieve the goals this study classifies hardware and software resources by cloud computing models and redesigns business processes based on cloud computing. Adopting cloud computing technology in a central archives management system can be a exemplary case for other archives management systems to improve system and business performance.

PCIA Cloud Service Modeling and Performance Analysis of Physical & Logical Resource Provisioning (PCIA 클라우드 서비스 모델링 및 자원 구성에 따른 성능 영향도 분석)

  • Yin, Binfeng;Kwak, Jong Wook
    • Journal of the Korea Society of Computer and Information
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    • 제19권2호
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    • pp.1-10
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    • 2014
  • Cloud computing provides flexible and efficient mass data analysis platform. In this paper, we define a new resource provisioning architecture in the public cloud, named PCIA. In addition, we provide a service model of PCIA and its new naming scheme. Our model selects the proper number of physical or virtual resources based on the requirements of clients. By the analysis of performance variation in the PCIA, we evaluate the relationship between performance variation and resource provisioning, and we present key standards for cloud system constructions, which can be an important resource provisioning criteria for both cloud service providers and clients.

A Study on the Archives Management System in Cloud Computing (클라우드 컴퓨팅 환경 영구기록물관리 시스템 구축 방안 연구)

  • Kim, Ki-Jung;Shin, Dong-Soo
    • Journal of Korean Society of Archives and Records Management
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    • 제18권3호
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    • pp.49-70
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    • 2018
  • This paper proposes a cloud system model for incorporating the existing Records Management System (RMS), Archives Management System (AMS), and Central Archives Management System (CAMS) into a cloud-based national records management system. To do this, research on concrete and stepwise ways to transform AMS, including CAMS, into a cloud computing environment was carried out. This study developed a cloud system design strategy and goal model to integrate national records-related systems into a single cloud system to share and utilize information resources, manage them efficiently, and reduce costs. In particular, this study analyzed technical security and operational security that are exposed in the cloud environment and suggested measures to solve them. As a result, cloud computing technology can be applied to achieve low-cost and high-efficiency effects.

Three-Dimensional Face Point Cloud Smoothing Based on Modified Anisotropic Diffusion Method

  • Wibowo, Suryo Adhi;Kim, Sungshin
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제14권2호
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    • pp.84-90
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    • 2014
  • This paper presents the results of three-dimensional face point cloud smoothing based on a modified anisotropic diffusion method. The focus of this research was to obtain a 3D face point cloud with a smooth texture and number of vertices equal to the number of vertices input during the smoothing process. Different from other methods, such as using a template D face model, modified anisotropic diffusion only uses basic concepts of convolution and filtering which do not require a complex process. In this research, we used 6D point cloud face data where the first 3D point cloud contained data pertaining to noisy x-, y-, and z-coordinate information, and the other 3D point cloud contained data regarding the red, green, and blue pixel layers as an input system. We used vertex selection to modify the original anisotropic diffusion. The results show that our method has improved performance relative to the original anisotropic diffusion method.

Mitigating Threats and Security Metrics in Cloud Computing

  • Kar, Jayaprakash;Mishra, Manoj Ranjan
    • Journal of Information Processing Systems
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    • 제12권2호
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    • pp.226-233
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    • 2016
  • Cloud computing is a distributed computing model that has lot of drawbacks and faces difficulties. Many new innovative and emerging techniques take advantage of its features. In this paper, we explore the security threats to and Risk Assessments for cloud computing, attack mitigation frameworks, and the risk-based dynamic access control for cloud computing. Common security threats to cloud computing have been explored and these threats are addressed through acceptable measures via governance and effective risk management using a tailored Security Risk Approach. Most existing Threat and Risk Assessment (TRA) schemes for cloud services use a converse thinking approach to develop theoretical solutions for minimizing the risk of security breaches at a minimal cost. In our study, we propose an improved Attack-Defense Tree mechanism designated as iADTree, for solving the TRA problem in cloud computing environments.

APPLICATION OF NEURAL NETWORK FOR THE CLOUD DETECTION FROM GEOSTATIONARY SATELLITE DATA

  • Ahn, Hyun-Jeong;Ahn, Myung-Hwan;Chung, Chu-Yong
    • Proceedings of the KSRS Conference
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    • 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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    • pp.34-37
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    • 2005
  • An efficient and robust neural network-based scheme is introduced in this paper to perform automatic cloud detection. Unlike many existing cloud detection schemes which use thresholding and statistical methods, we used the artificial neural network methods, the multi-layer perceptrons (MLP) with back-propagation algorithm and radial basis function (RBF) networks for cloud detection from Geostationary satellite images. We have used a simple scene (a mixed scene containing only cloud and clear sky). The main results show that the neural networks are able to handle complex atmospheric and meteorological phenomena. The experimental results show that two methods performed well, obtaining a classification accuracy reaching over 90 percent. Moreover, the RBF model is the most effective method for the cloud classification.

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