• KIISE Transactions on Computing Practices
• /
• v.22 no.8
• /
• pp.345-350
• /
• 2016

Cloud computing services have different characteristics from the traditional computing environment such as resource sharing, virtualization, etc. These characteristics of cloud computing environment necessitate specific properties such as user identify, access control, security control property, etc. Recently, Yoo proposed an attribute-based authentication scheme for secure cloud computing. However, Yoo's authentication scheme is vulnerable to customer attack and an adversary can modify the authentication request message. In this paper, we propose a secure and efficient attribute-based authentication scheme for cloud computing based on Yoo's scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.12
• /
• pp.2294-2314
• /
• 2011

The key issue in providing fast and reliable access on cloud services is the effective management of resources in a cloud system. However, the high variation in cloud service access rates affects the system performance considerably when there are no default routines to handle this type of occurrence. Adaptive techniques are used in resource management to support robust systems and maintain well-balanced loads within the servers. This paper presents an adaptive resource management for cloud systems which supports the integration of intelligent methods to promote quality of service (QoS) in provisioning of cloud services. A technique of dynamically assigning cloud services to a group of cloud servers is proposed for the adaptive resource management. Initially, cloud services are collected based on the excess cloud services load and then these are deployed to the assigned cloud servers. The assignment function uses the proposed proportional ordering which efficiently assigns cloud services based on its resource consumption. The difference in resource consumption rate in all nodes is analyzed periodically which decides the execution of service assignment. Performance evaluation showed that the proposed dynamic service assignment (DSA) performed best in throughput performance compared to other resource allocation algorithms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.10a
• /
• pp.366-369
• /
• 2014

Recently been viewed as a core technology of the IT industry, cloud computing services. It is expected that the market for cloud services industry showed a growth rate of 18.9% annually, to form a scale of $ 1,330 billion dollars in 2013, and to form a 1,768 billion dollars in 2015. Growth of cloud computing services industry, provides the operational efficiency and reduce costs for many companies, but the risks associated with it is also increasing. There is a problem that phenomenon is to lose control of the data on features of the cloud service, more data is gathered in one place, when a failure occurs, it is removed simultaneously the data of all devices. therefore, in the present paper is investigate the area a quick recovery with up to the problem and secure data storage INT the cloud computing service is available in only the data in the cloud service possible.

• International Journal of Computer Science & Network Security
• /
• v.21 no.11
• /
• pp.345-353
• /
• 2021

Cloud computing represent a new era of computing that's forms through the combination of service-oriented architecture (SOA), Internet and grid computing with virtualization technology. Virtualization is a concept through which every cloud is enable to provide on-demand services to the users. Most IT service provider adopt cloud based services for their users to meet the high demand of computation, as it is most flexible, reliable and scalable technology. Energy based performance tradeoff become the main challenge in cloud computing, as its acceptance and popularity increases day by day. Cloud data centers required a huge amount of power supply to the virtualization of servers for maintain on- demand high computing. High power demand increase the energy cost of service providers as well as it also harm the environment through the emission of CO₂. An optimization of cloud computing based on energy-performance tradeoff is required to obtain the balance between energy saving and QoS (quality of services) policies of cloud. A study about power usage of resources in cloud data centers based on workload assign to them, says that an idle server consume near about 50% of its peak utilization power [1]. Therefore, more number of underutilized servers in any cloud data center is responsible to reduce the energy performance tradeoff. To handle this issue, a lots of research proposed as energy efficient algorithms for minimize the consumption of energy and also maintain the SLA (service level agreement) at a satisfactory level. VM (virtual machine) consolidation is one such technique that ensured about the balance of energy based SLA. In the scope of this paper, we explore reinforcement with fuzzy logic (RFL) for VM consolidation to achieve energy based SLA. In this proposed RFL based active VM consolidation, the primary objective is to manage physical server (PS) nodes in order to avoid over-utilized and under-utilized, and to optimize the placement of VMs. A dynamic threshold (based on RFL) is proposed for over-utilized PS detection. For over-utilized PS, a VM selection policy based on fuzzy logic is proposed, which selects VM for migration to maintain the balance of SLA. Additionally, it incorporate VM placement policy through categorization of non-overutilized servers as- balanced, under-utilized and critical. CloudSim toolkit is used to simulate the proposed work on real-world work load traces of CoMon Project define by PlanetLab. Simulation results shows that the proposed policies is most energy efficient compared to others in terms of reduction in both electricity usage and SLA violation.

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

• Journal of Advanced Navigation Technology
• /
• v.17 no.1
• /
• pp.63-68
• /
• 2013

Recently, companies seek a way to overcome their financial crisis by reducing costs in the field of IT. In such a circumstance, cloud computing is rapidly emerging as an optimal solution to the crisis. Even in a digital forensic investigation, whether users of an investigated system have used a cloud service is a very important factor in selecting additional investigated subjects. When a user has used cloud services, such as Daum Cloud and Google Docs, it is possible to connect to the could service from a remote place by acquiring the user's log-in information. In such a case, evidence data should be collected from the remote place for an efficient digital forensic investigation, and it is needed to conduct research on the collection and analysis of data from various kinds of cloud services. Thus, this study suggested a digital forensic framework considering cloud environments by investigating collection and analysis techniques for each cloud service.

• International Journal of Computer Science & Network Security
• /
• v.23 no.5
• /
• pp.65-72
• /
• 2023

Cloud Computing is one of the current research areas in computer science. Recently, Cloud is the buzz word used everywhere in IT industries; It introduced the notion of 'pay as you use' and revolutionized developments in IT. The rapid growth of modernized cloud computing leads to 24×7 accessing of e-resources from anywhere at any time. It offers storage as a service where users' data can be stored on a cloud which is managed by a third party who is called Cloud Service Provider (CSP). Since users' data are managed by a third party, it must be encrypted ensuring confidentiality and privacy of the data. There are different types of cryptographic algorithms used for cloud security; in this article, the algorithms and their security measures are discussed.

• The Journal of Korean Association of Computer Education
• /
• v.14 no.2
• /
• pp.75-82
• /
• 2011

Cloud computing is a computing paradigm that provides user's services anywhere, anytime in a virtualized form composed of large computing resources based on internet or intranet. In Cloud computing environments, reliability of system is impact factor because many applications handle large data. In this paper, we propose an adaptive scheduling technique based on reliability with fault tolerance that manages resource variable and resolves problems(change of user's requirement, failure occurrence) in Cloud computing environment. Futhermore, we verified the performance of the proposed scheduling through experiments in CloudSim Simulation.

• Journal of Information Processing Systems
• /
• v.14 no.1
• /
• pp.239-251
• /
• 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)
• /
• v.16 no.6
• /
• pp.1892-1912
• /
• 2022

With the massive demand and growth of cloud computing, virtualization plays an important role in providing services to end-users efficiently. However, with the increase in services over Cloud Computing, it is becoming more challenging to manage and run multiple Virtual Machines (VMs) in Cloud Computing because of excessive power consumption. It is thus important to overcome these challenges by adopting an efficient technique to manage and monitor the status of VMs in a cloud environment. Reduction of power/energy consumption can be done by managing VMs more effectively in the datacenters of the cloud environment by switching between the active and inactive states of a VM. As a result, energy consumption reduces carbon emissions, leading to green cloud computing. The proposed Efficient Dynamic VM Scheduling approach minimizes Service Level Agreement (SLA) violations and manages VM migration by lowering the energy consumption effectively along with the balanced load. In the proposed work, VM Scheduling for Efficient Dynamically Migrated VM (VMS-EDMVM) approach first detects the over-utilized host using the Modified Weighted Linear Regression (MWLR) algorithm and along with the dynamic utilization model for an underutilized host. Maximum Power Reduction and Reduced Time (MPRRT) approach has been developed for the VM selection followed by a two-phase Best-Fit CPU, BW (BFCB) VM Scheduling mechanism which is simulated in CloudSim based on the adaptive utilization threshold base. The proposed work achieved a Power consumption of 108.45 kWh, and the total SLA violation was 0.1%. The VM migration count was reduced to 2,202 times, revealing better performance as compared to other methods mentioned in this paper.