• Journal of Information Technology Services
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• v.14 no.2
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• pp.289-314
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• 2015

Recently, Most of the companies and government offices are under consideration about the adoption of cloud office service to actualize the smart work policies. Comparing with traditional office software, a cloud office service have the advantage of the method of payment and coming over the physical limitations. Many cloud office service users tend to adopt an official evaluated the service without doubt. However after deciding to adopt cloud office service, many users are faced with a variety of problems and difficulties practically. In this study, researchers carried out interview about those problems and difficulties after adopting a cloud office service. Consequently, there are several problems and difficulties such as compatibility, document security, document lost and maladjusted to the new graphic user interface between traditional office software and a cloud office service. A cloud office service have still several advantages not only a competitive price but also ubiquitous attributes. Thus, researchers need to study about what kinds of reason variables can solve those problems and difficulties. In existing research, DeLone & McLean have suggested information system success model. They use three independent variables which are system quality, information quality, service quality. Parameters are user satisfaction, intention to use and use. Lastly, dependent variables are net benefits. However in this study, we need to change the scope of measurement. In other words, we have to replace parameters with dependent variables. Simply, user satisfaction, intention to use and use is going to be dependent variables. There are several reasons why we need changing variables. First, we aim at giving a some suggestions to a cloud service providers which independent variables do not work to satisfy for the users. Second, we need to find out how to maximize cloud office service user's satisfaction and intention to use. Third, we should firstly know that relationship between independent variables and dependent variables. Finally, those research results give for the cloud office service provider to solve the cloud office service adopting problems and difficulties.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.473-491
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• 2014

There is a growing interest for 'Cloud computing' to cut costs, and help the users focus on their core business instead of being impeded by IT obstacles. As it became IT version 3.0 which represents the era of cloud services and the dominance of a new kind of IT service provider, cloud service providers (CSPs)' role is more critical as a trusted IT advisor to include cloud migration and integration expertise. However, previous literatures related to cloud computing service have mainly analyzed from customers, although it is hard for customers to totally understand the complex and diverse cloud ecosystem. Therefore, it is an urgent task to mitigate the inhibitory factors in providing the cloud services for activating cloud industry. This study, an exploratory research based on interviews, has derived factors of promoting and hindering the activation of cloud computing from the provider's perspective, and has analyzed a sequence of cause and effect for each factor. For this, the casual loop diagram was developed to deduce key issues, and propose an alternative. The results of this study are expected to help activate 'Cloud computing' in Korea by minimizing the potential negative effects of activating 'Cloud computing' industry.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.4
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• pp.161-168
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• 2015

It is difficult to provide proper cloud services for cloud users, because the number of cloud services are increasing and the type of cloud services are diversifying. To overcome this problem, the concept of cloud service broker is presented to mediate cloud services between cloud providers and tenant. The most important role of cloud service broker is to finding cloud services that fulfill requirements of tenant. However, current existing cloud service broker conduct passive requirements analysis process with cloud service expert's assistance. In addition, the systematic functional and non-functional requirement analysis is insufficient. Therefore, we need the new methods for requirement analysis to find nearest service that matches with requirement of tenant. In this paper, we apply pairwise comparison from AHP method to analyze requirement automatically and systematically. It calculates score of service by comparing requirement with service specification, calculating importance rate, and so on.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1258-1275
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• 2023

Cloud computing is a new technology that has adapted to the traditional way of service providing. Service providers are responsible for managing the allocation of resources. Selecting suitable containers and bandwidth for job scheduling has been a challenging task for the service providers. There are several existing systems that have introduced many algorithms for resource allocation. To overcome these challenges, the proposed system introduces an Optimized Task Scheduling Algorithm with Deep Learning (OTS-DL). When a job is assigned to a Cloud Service Provider (CSP), the containers are allocated automatically. The article segregates the containers as' Long-Term Container (LTC)' and 'Short-Term Container (STC)' for resource allocation. The system leverages an 'Optimized Task Scheduling Algorithm' to maximize the resource utilisation that initially inquires for micro-task and macro-task dependencies. The bottleneck task is chosen and acted upon accordingly. Further, the system initializes a 'Deep Learning' (DL) for implementing all the progressive steps of job scheduling in the cloud. Further, to overcome container attacks and errors, the system formulates a Container Convergence (Fault Tolerance) theory with high-level security. The results demonstrate that the used optimization algorithm is more effective for implementing a complete resource allocation and solving the large-scale optimization problem of resource allocation and security issues.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.4
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• pp.597-613
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• 2024

MyData is an approach of personal data management, which grants data subjects the right to decide how to use and where to provide their data. With the explicit consent of the subjects, service providers can collect scattered data from data sources and offer personalized services based on the collected data. In existing service models, personal data saved in data storage can be shared with data processors of service providers or third parties. However, once personal data are transferred to third-party processors, it is difficult for data subjects to trace and control their personal data. Therefore, in this paper, we propose a cloud model where both data storage and processor are located within a single cloud, ensuring that data do not leave the cloud.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.53-58
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• 2013

Due to the wide spread of the perception of cloud computing, the usage of cloud computing is increasing globally. Cloud computing is able to converge the various industrial domains based on ICT and it is more and more popular because it has a lot of benefits such as cost savings etc. in global economic recession. However, if cloud computing service is to achieve its potential, it is necessary to clearly understand the critical issues such as service security, performance and availability and so on from the perspectives of the providers and the consumers of the cloud service. In addition, customers focus on how to get and use the safe and reliable cloud service. In order to meet these problems, Korea cloud service certification system and Japanese ASP-SaaS-Cloud certification system were performed in each country. This paper aims at comparing and analyzing between them and describing the difference. Eventually, we propose the improvement strategy of Korea cloud service certification system based on the comparison results between them.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5780-5802
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• 2017

Cloud computing system consists of distributed resources in a dynamic and decentralized environment. Therefore, using cloud computing resources efficiently and getting the maximum profits are still challenging problems to the cloud service providers and cloud service users. It is important to provide the efficient scheduling. To schedule cloud resources, numerous heuristic algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Cuckoo Search (CS) algorithms have been adopted. The paper proposes a Modified Particle Swarm Optimization (MPSO) algorithm to solve the above mentioned issues. We first formulate an optimization problem and propose a Modified PSO optimization technique. The performance of MPSO was evaluated against PSO, and GA. Our experimental results show that the proposed MPSO minimizes the task execution time, and maximizes the resource utilization rate.

• Journal of Information Processing Systems
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• v.10 no.2
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• pp.240-255
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• 2014

Cloud computing has increasingly been drawing attention these days. Each big company in IT hurries to get a chunk of meat that promises to be a whopping market in the future. At the same time, information is always associated with security and risk problems. Nowadays, the handling of these risks is no longer just a technology problem, with a good deal of literature focusing on risk or security management and framework in the information system. In this paper, we find the specific business meaning of the BMIS model and try to apply and leverage this model to cloud risk. Through a previous study, we select and determine the causal risk factors in cloud service, which are also known as CSFs (Critical Success Factors) in information management. Subsequently, we distribute all selected CSFs into the BMIS model by mapping with ten principles in cloud risk. Finally, by using the leverage points, we try to leverage the model factors and aim to make a resource-optimized, dynamic, general risk control business model for cloud service providers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4204-4222
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• 2015

Cloud is the latest buzz word in the internet community among developers, consumers and security researchers. There have been many attacks on the cloud in the recent past where the services got interrupted and consumer privacy has been compromised. Denial of Service (DoS) attacks effect the service availability to the genuine user. Customers are paying to use the cloud, so enhancing the availability of services is a paramount task for the service provider. In the presence of DoS attacks, the availability is reduced drastically. Such attacks must be detected and prevented as early as possible and the power of computational approaches can be used to do so. In the literature, machine learning techniques have been used to detect the presence of attacks. In this paper, a novel approach is proposed, where intelligent rule based feature selection and classification are performed for DoS attack detection in the cloud. The performance of the proposed system has been evaluated on an experimental cloud set up with real time DoS tools. It was observed that the proposed system achieved an accuracy of 98.46% on the experimental data for 10,000 instances with 10 fold cross-validation. By using this methodology, the service providers will be able to provide a more secure cloud environment to the customers.

• Journal of Korean Society for Quality Management
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• v.41 no.3
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• pp.381-394
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• 2013

Purpose: Nowadays, Mobile Cloud Storage services are used widely. For sustainable use of this service, we need to determine what factors affect satisfaction. Therefore, the purpose of this study is to identify the factors that influence satisfaction. Methods: To analyze factors that influence satisfaction, this study sets the factors into three dimensions such as service quality, perceived risk, and individual characteristics and analyze the causal relationship between influence factors and satisfaction through Structural Equation Model. Results: The results of this study are as follows; among service quality, user interface and reliability influenced satisfaction, but adaptability did not have any influence. Perceived risk of illegal access had a negative influence on satisfaction, while perceived risk of privacy leakage did not have significant influence on satisfaction in perceived risk. At last, self-efficacy had a significant influence on satisfaction. Conclusion: We identified the influence factors that influence satisfaction. Our findings will be necessary for Mobile Cloud Storage service providers to strengthen their service.