• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4742-4770
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• 2019

Cloud computing provides a broad range of services like operating systems, hardware, software and resources. Availability of these services encourages data owners to outsource their intensive computations and massive data to the cloud. However, considering the untrusted nature of cloud server, it is essential to encrypt the data before outsourcing it to the cloud. Unfortunately, this leads to a challenge when it comes to providing search functionality for encrypted data located in the cloud. To address this challenge, this paper presents a public key encryption with equality test for heterogeneous systems (PKE-ET-HS). The PKE-ET-HS scheme simulates certificateless public encryption with equality test (CLE-ET) with the identity-based encryption with equality test (IBE-ET). This scheme provides the authorized cloud server the right to actuate the equivalence of two messages having their encryptions performed under heterogeneous systems. Basing on the random oracle model, we construct the security of our proposed scheme under the bilinear Diffie-Hellman (BDH) assumption. Eventually, we evaluate the size of storage, computation complexities, and properties with other related works and illustrations indicate good performance from our scheme.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.23 no.3
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• pp.57-84
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• 2012

With the advent of Big data era unleashed by tremendous increase of structured and unstructured data, a library needs an effective method to store, manage and preserve various information resources. Also, needs of collaboration of libraries are continuously increased in digital environment. As an effective method to handle the changes and challenges in libraries, interest on cloud computing is growing more and more. This study aims to propose a method to introduce cloud computing in libraries. To achieve the goals, this study performed the literature review to analyze problems of existing library systems. Also, this study proposed considerations, expectations, service scenario, phased strategy to introduce cloud computing in libraries. Based on the results extracted from cases that libraries have introduced cloud computing-based systems, this study proposed introduction strategy and specific applying areas in library works as considered features of cloud computing models. The proposed phased strategy and service scenario may reduce time and effort in the process of introduction of cloud computing and maximize the effect of cloud computing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3663-3679
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• 2020

Scheduling plays a dynamic role in cloud computing in generating as well as in efficient distribution of the resources of each task. The principle goal of scheduling is to limit resource starvation and to guarantee fairness among the parties using the resources. The demand for resources fluctuates dynamically hence the prearranging of resources is a challenging task. Many task-scheduling approaches have been used in the cloud-computing environment. Security in cloud computing environment is one of the core issue in distributed computing. We have designed a deep learning-based security model for scheduling tasks in cloud computing and it has been implemented using CloudSim 3.0 simulator written in Java and verification of the results from different perspectives, such as response time with and without security factors, makespan, cost, CPU utilization, I/O utilization, Memory utilization, and execution time is compared with Round Robin (RR) and Waited Round Robin (WRR) algorithms.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.3
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• pp.70-76
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• 2012

This research tested how the perceived risk and the trust affect the usage intention of the cloud computing. To this end, this research setups a research model and tests it with the statistic tools. In order to build the model, TAM (Technology Acceptance Model) and UTAUT (Unified Theory of Acceptance and Use of Technology) were employed and, the factors such as the perceived risk, the trust and the intention of the cloud computing use were derived. This research finds that the perceived risk does not affect the intention of usage. Also the perceived risk has the negative effect for the trust. Thus this research has the following suggestions.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.467-475
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• 2012

Cloud computing services are known that they have many advantages from the point of view in economic saving, scalability, security, sharing and accessibility. So their applications are extending from simple office systems to the expert system for scientific computing. However, research or computing technology development in the geo-spatial fields including remote sensing applications are the beginning stage. In this work, the previously implemented smartphone app for image processing was first migrated to mobile cloud computing linked to Amazon web services. As well, parallel programming was applied for improving operation performance. Industrial needs and technology development cases in terms of mobile cloud computing services are being increased. Thus, a performance testing on a satellite image processing module was carried out as the main purpose of this study. Types of implementation or services for mobile cloud varies. As the result of this testing study in a given condition, the performance of cloud computing server was higher than that of the single server without cloud service. This work is a preliminary case study for the further linkage approach for mobile cloud and satellite image processing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1265-1278
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• 2017

Dynamic task scheduling is one of the most popular research topics in the cloud computing field. The cloud scheduler dynamically provides VM resources to variable cloud tasks with different scheduling strategies in cloud computing. In this study, we utilized a valid model to describe the dynamic changes of both computing facilities (such as hardware updating) and request task queuing. We built a novel approach called Policy Iteration Scheduling (PIS) to globally optimize the independent task scheduling scheme and minimize the total execution time of priority tasks. We performed experiments with randomly generated cloud task sets and varied the performance of VM resources using Poisson distributions. The results show that PIS outperforms other popular schedulers in a typical cloud computing environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.1998-2014
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• 2016

In recent years, cloud computing services based on smart phones and other mobile terminals have been a rapid development. Cloud computing has the advantages of mass storage capacity and high-speed computing power, and it can meet the needs of different types of users, and under the background, mobile cloud computing (MCC) is now booming. In this paper, we have put forward a new classification-based virtual machine placement (CBVMP) algorithm for MCC, and it aims at improving the efficiency of virtual machine (VM) allocation and the disequilibrium utilization of underlying physical resources in large cloud data center. By simulation experiments based on CloudSim cloud platform, the experimental results show that the new algorithm can improve the efficiency of the VM placement and the utilization rate of underlying physical resources.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.239-251
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• 2018

In existing cloud services, information security and privacy concerns have been worried, and have become one of the major factors that hinder the popularization and promotion of cloud computing. As the cloud computing infrastructure, the security of virtual machine systems is very important. This paper presents an immune-inspired intrusion detection model in virtual machines of cloud computing environment, denoted I-VMIDS, to ensure the safety of user-level applications in client virtual machines. The model extracts system call sequences of programs, abstracts them into antigens, fuses environmental information of client virtual machines into danger signals, and implements intrusion detection by immune mechanisms. The model is capable of detecting attacks on processes which are statically tampered, and is able to detect attacks on processes which are dynamically running. Therefore, the model supports high real time. During the detection process, the model introduces information monitoring mechanism to supervise intrusion detection program, which ensures the authenticity of the test data. Experimental results show that the model does not bring much spending to the virtual machine system, and achieves good detection performance. It is feasible to apply I-VMIDS to the cloud computing platform.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.1063-1075
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• 2022

In recent years, container techniques have been broadly applied to cloud computing systems to maximize their efficiency, flexibility, and economic feasibility. Concurrently, studies have also been conducted to ensure the security of cloud computing. Among these studies, moving-target defense techniques using the high agility and flexibility of cloud-computing systems are gaining attention. Moving-target defense (MTD) is a technique that prevents various security threats in advance by proactively changing the main attributes of the protected target to confuse the attacker. However, an analysis of existing MTD techniques revealed that, although they are capable of deceiving attackers, MTD techniques have practical limitations when applied to an actual cloud-computing system. These limitations include resource wastage, management complexity caused by additional function implementation and system introduction, and a potential increase in attack complexity. Accordingly, this paper proposes a software-defined MTD system that can flexibly apply and manage existing and future MTD techniques. The proposed software-defined MTD system is designed to correctly define a valid mutation range and cycle for each moving-target technique and monitor system-resource status in a software-defined manner. Consequently, the proposed method can flexibly reflect the requirements of each MTD technique without any additional hardware by using a software-defined approach. Moreover, the increased attack complexity can be resolved by applying multiple MTD techniques.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1281-1292
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• 2020

More and more cloud computing services are being applied in various fields; however, it is difficult for users and cloud computing service platforms to establish trust among each other. The trust value cannot be measured accurately or effectively. To solve this problem, we design a service-oriented cloud trust assessment model using a cloud model. We also design a subjective preference weight allocation (SPWA) algorithm. A flexible weight model is advanced by combining SPWA with the entropy method. Aiming at the fuzziness and subjectivity of trust, the cloud model is used to measure the trust value of various cloud computing services. The SPWA algorithm is used to integrate each evaluation result to obtain the trust evaluation value of the entire cloud service provider.