• Journal of Advanced Navigation Technology
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• v.13 no.5
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• pp.781-786
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• 2009

The cloud computing environment is a new trend of web based application parts. It can be IT business model that is able to easily support learning service and allocate resources through the internet to users. U-learning also is a maximal model with efficiency of the internet based learning. Thus, in this research, we proposed a design of u-learning's teaching and learning model that is applying the internet based learning. Proposal method is to fit u-learning and has 7 steps: Preparing, planning, gathering, learning process, analysis and evaluation, and feedback. We make a cloud u-learning server and cloud LMS to process and manage the service. And We also make a mobile devices meta data to aware the model.

• ETRI Journal
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• v.39 no.1
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• pp.135-144
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• 2017

Recently, mobile phones have been recognized as the most convenient type of mobile payment device. However, they have some security problems; therefore, mobile devices cannot be used for unauthorized transactions using anonymous data by unauthenticated users in a cloud environment. This paper suggests a mobile payment system that uses a certificate mode in which a user receives a paperless receipt of a product purchase in a cloud environment. To address mobile payment system security, we propose the transaction certificate mode (TCM), which supports mutual authentication and key management for transaction parties. TCM provides a software token, the transaction certificate token (TCT), which interacts with a cloud self-proxy server (CSPS). The CSPS shares key management with the TCT and provides simple data authentication without complex encryption. The proposed self-creating protocol supports TCM, which can interactively communicate with the transaction parties without accessing a user's personal information. Therefore, the system can support verification for anonymous data and transaction parties and provides user-based mobile payments with a paperless receipt.

• Journal of Advanced Navigation Technology
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• v.16 no.1
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• pp.116-121
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• 2012

This research aimed an application method to connect traditional culture and information technology that is one of the digital convergence area. For this purpose, we proposed cloud digital archive framework for traditional culture. Actually, cloud computing environment is one of new technology trend and would be a important keyword for information technology. This research focus on functional framework that is able to support service in cloud computing environment to connect pansori archive model, one of traditional culture. We also make a data structure and metadata by each characteristics, and insert a service framework to support pansori archive. This structure consists of data evaluation, preservation, and access process. This archive has a relation model with digital archive and metadata.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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• pp.1712-1732
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• 2011

Cloud provides dynamically scalable virtualized computing resources as a service over the Internet. To achieve higher resource utilization over virtualization technology, an optimized strategy that deploys virtual machines on physical machines is needed. That is, the total number of active physical host nodes should be dynamically changed to correspond to their resource usage rate, thereby maintaining optimum utilization of physical machines. In this paper, we propose a pattern-based prediction model for resource provisioning which facilitates best possible resource preparation by analyzing the resource utilization and deriving resource usage patterns. The focus of our work is on predicting future resource requests by optimized dynamic resource management strategy that is applied to a virtualized data center in a Cloud computing environment. To this end, we build a prediction model that is based on user request patterns and make a prediction of system behavior for the near future. As a result, this model can save time for predicting the needed resource amount and reduce the possibility of resource overuse. In addition, we studied the performance of our proposed model comparing with conventional resource provisioning models under various Cloud execution conditions. The experimental results showed that our pattern-based prediction model gives significant benefits over conventional models.

• Journal of the Korea Society of Computer and Information
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• v.19 no.2
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• pp.67-75
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• 2014

In this paper, we proposed offloading delay method which determines effectively offloading timing by measuring of handoff delay and offloading time at mobile node side in mobile environment. The propose method measures each of handoff delay and offloading time and making decision of proper offloading timing on mobile node side. Therefore, it is possible to support cloud computing without changing previous implemented cloud computing structure for fixed node in a mobile environment. We compare the energy consumption of server and node to analyze efficiency of proposed method by using existing method of energy consumption measurement. Simulation results shows the reducing energy consumption more than previous method and operation time similar to previous method.

• International Journal of Advanced Culture Technology
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• v.9 no.3
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• pp.327-333
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• 2021

Inbody is a tool for measuring health information with high reliability and accuracy to analyze body composition. Unlike the existing method of storing/processing and outputting data on the server side, the health information generated by InBody requires accurate support for health sharing and data analysis services using mobile devices. However, in the process of transmitting body composition measurement information to a mobile service, a problem may occur in data transmission/reception processing. The reason for this is that, since the network network in the cloud environment is used, if the connection is cut off or the connection is changed, it is necessary to provide a global service, not a temporary area, focusing on the mobility of InBody information. In addition, since InBody information is transmitted to mobile devices, a standard schema should be defined in the mobile cloud environment to enable information transfer between standardized InBody data and mobile devices. We propose a mobile cloud system using EMRA(Extended Metadata Registry Access) in which a mobile device processes and transmits body data generated in the inbody and manages the data of each local organization with a standard schema. The proposed system processes the data generated in InBody and converts it into a standard schema using EMRA so that standardized data can be transmitted. In addition, even when the mobile device moves through the area, the coordinator subsystem is in charge of providing access services. In addition, EMRA is applied to the collision problem due to schema heterogeneity occurring in the process of accessing data generated in InBody.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3794-3820
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• 2019

In recent years, a cloud environment with the ability to detect illegal behaviours along with a secured data storage capability is much needed. This study presents a cloud storage framework, wherein a 128-bit encryption key has been generated by combining deoxyribonucleic acid (DNA) cryptography and the Hill Cipher algorithm to make the framework unbreakable and ensure a better and secured distributed cloud storage environment. Moreover, the study proposes a DNA-based encryption technique, followed by a 256-bit secure socket layer (SSL) to secure data storage. The 256-bit SSL provides secured connections during data transmission. The data herein are classified based on different qualitative security parameters obtained using a specialized fuzzy-based classification technique. The model also has an additional advantage of being able to decide on selecting suitable storage servers from an existing pool of storage servers. A fuzzy-based technique for order of preference by similarity to ideal solution (TOPSIS) multi-criteria decision-making (MCDM) model has been employed for this, which can decide on the set of suitable storage servers on which the data must be stored and results in a reduction in execution time by keeping up the level of security to an improved grade.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.145-164
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• 2023

Cloud computing offers a platform that is both adaptable and scalable, making it ideal for outsourcing data for sharing. Various organizations outsource their data on cloud storage servers for availing management and sharing services. When the organizations outsource the data, they lose direct control on the data. This raises the privacy and security concerns. Cryptographic encryption methods can secure the data from the intruders as well as cloud service providers. Data owners may also specify access control policies such that only the users, who satisfy the policies, can access the data. Attribute based access control techniques are more suitable for the cloud environment as they cover large number of users coming from various domains. Multi-authority attribute-based encryption (MA-ABE) technique is one of the propitious attribute based access control technique, which allows data owner to enforce access policies on encrypted data. The main aim of this paper is to comprehensively survey various state-of-the-art MA-ABE schemes to explore different features such as attribute and key management techniques, access policy structure and its expressiveness, revocation of access rights, policy updating techniques, privacy preservation techniques, fast decryption and computation outsourcing, proxy re-encryption etc. Moreover, the paper presents feature-wise comparison of all the pertinent schemes in the field. Finally, some research challenges and directions are summarized that need to be addressed in near future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.422-424
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• 2021

In this paper, it leads the approach of fusing multiple RGB cameras for visual objects recognition based on deep learning with convolution neural network and 3D Light Detection and Ranging (LiDAR) to observe the environment and match into a 3D world in estimating the distance and position in a form of point cloud map. The goal of perception in multiple cameras are to extract the crucial static and dynamic objects around the autonomous vehicle, especially the blind spot which assists the AV to navigate according to the goal. Numerous cameras with object detection might tend slow-going the computer process in real-time. The computer vision convolution neural network algorithm to use for eradicating this problem use must suitable also to the capacity of the hardware. The localization of classified detected objects comes from the bases of a 3D point cloud environment. But first, the LiDAR point cloud data undergo parsing, and the used algorithm is based on the 3D Euclidean clustering method which gives an accurate on localizing the objects. We evaluated the method using our dataset that comes from VLP-16 and multiple cameras and the results show the completion of the method and multi-sensor fusion strategy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.38-57
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• 2016

Service discovery is one of the major challenges in cloud computing environment with a large number of service providers and heterogeneous services. Non-uniform naming conventions, varied types and features of services make cloud service discovery a grueling problem. With the proliferation of cloud services, it has been laborious to find services, especially from Internet-based service repositories. To address this issue, services are crawled and clustered according to their similarity. The clustered services are maintained as a catalogue in which the data published on the cloud provider's website are stored in a standard format. As there is no standard specification and a description language for cloud services, new efficient and intelligent mechanisms to discover cloud services are strongly required and desired. This paper also proposes a key-value representation to describe cloud services in a formal way and to facilitate matching between offered services and demand. Since naïve users prefer to have a query in natural language, semantic approaches are used to close the gap between the ambiguous user requirements and the service specifications. Experimental evaluation measured in terms of precision and recall of retrieved services shows that the proposed approach outperforms existing methods.