scholarly journals V-MGSM: A Multilevel and Grouping Security Virtualization Model for Mobile Internet Service

2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Hui Zhu ◽  
Yingfang Xue ◽  
Xiaofeng Chen ◽  
Qiang Li ◽  
Hui Li
Keyword(s):  
Cloud Computing ◽  
Secure Communication ◽  
Virtual Machines ◽  
Cloud Service ◽  
Mobile Internet ◽  
Security Requirements ◽  
Security And Privacy ◽  
Security Level ◽  
Security Model ◽  
Internet Service

With the pervasiveness of smart phones and the advance of Mobile Internet, more and more Mobile Internet services migrated to the cloud service platform for better user experience. As one of the most indispensable components of the cloud computing infrastructure, virtualization technology has attracted considerable interest recently. However, the flourish of virtualization still faces many challenges in information security. In this paper, we propose a novel architecture, called multilevel and grouping security model for virtualization (V-MGSM), for the security of resources in cloud computing platform. Specifically, to fulfill the balance between information sharing and privacy preservation, the virtual machines (VMs) are divided into diverse groups based on their corresponding entities, and each VM in the same group is assigned to different security level according to security requirements. Besides, the operation between VMs is based on mandatory access control mechanism. Detailed security analysis shows that the proposed V-MGSM can provide a secure communication mechanism for VMs and implement the synchronous updates of the borrowed data. Ultimately, we implement V-MGSM in Xen for experiments, and the results demonstrate that V-MGSM can indeed achieve data security and privacy protection efficiently for Mobile Internet service.

scholarly journals Improvement of Privacy and Security in Hybrid Cloud with Attribute Group Based Access Control

2019 ◽  
pp. 57-61
Author(s):  
Kayalvili S ◽  
Sowmitha V
Keyword(s):  
Cloud Computing ◽  
Access Control ◽  
Data Storage ◽  
Service Providers ◽  
Cloud Service ◽  
Security Requirements ◽  
Security And Privacy ◽  
Data Outsourcing ◽  
Privacy And Security ◽  
Control Approach

Cloud computing enables users to accumulate their sensitive data into cloud service providers to achieve scalable services on-demand. Outstanding security requirements arising from this means of data storage and management include data security and privacy. Attribute-based Encryption (ABE) is an efficient encryption system with fine-grained access control for encrypting out-sourced data in cloud computing. Since data outsourcing systems require flexible access control approach Problems arises when sharing confidential corporate data in cloud computing. User-Identity needs to be managed globally and access policies can be defined by several authorities. Data is dual encrypted for more security and to maintain De-Centralization in Multi-Authority environment.

Cloud Security

2014 ◽  
pp. 97-117
Keyword(s):  
Cloud Computing ◽  
Service Delivery ◽  
Cloud Service ◽  
Shared Responsibility ◽  
Security And Privacy ◽  
Security Model ◽  
Service Delivery Models ◽  
Responsibility Model ◽  
Orthogonal Dimension ◽  
Delivery Models

Although cloud computing has been widely accepted in the enterprise, and its usage is growing exponentially, security and privacy are big challenges for adoption and survival of cloud computing. Security has two facets in the cloud computing landscape, that is there are pros and there are cons. Security is obligatory for all service delivery models of cloud computing. Additionally, cloud deployment options are another orthogonal dimension to the cloud service delivery models. With the adoption of cloud computing, a large part of network, system, applications, and data will move under provider control. The cloud service delivery model will create several virtual perimeters as well as a security model with responsibilities shared between the customer and the provider. This shared responsibility model will bring new security management challenges to the organization. This chapter discusses these issues and enumerates some initiatives to address them.

scholarly journals ALGORITHM FOR TASK CONSOLIDATION IN CLOUD COMPUTING: A COMPARATIVE SURVEY

2018 ◽  
Vol 6 (5) ◽  
pp. 340-345
Author(s):  
Rajat Pugaliya ◽  
Madhu B R
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Resource Utilization ◽  
Service Provider ◽  
Virtual Machines ◽  
Cloud Service ◽  
Cloud Service Provider ◽  
Dynamic Task ◽  
Main Challenge ◽  
High Level

Cloud Computing is an emerging field in the IT industry. Cloud computing provides computing services over the Internet. Cloud Computing demand increasing drastically, which has enforced cloud service provider to ensure proper resource utilization with less cost and less energy consumption. In recent time various consolidation problems found in cloud computing like the task, VM, and server consolidation. These consolidation problems become challenging for resource utilization in cloud computing. We found in the literature review that there is a high level of coupling in resource utilization, cost, and energy consumption. The main challenge for cloud service provider is to maximize the resource utilization, reduce the cost and minimize the energy consumption. The dynamic task consolidation of virtual machines can be a way to solve the problem. This paper presents the comparative study of various task consolidation algorithms.

scholarly journals An analysis of software aging in cloud environment

2020 ◽  
Vol 10 (6) ◽  
pp. 5985
Author(s):  
Shruthi P. ◽  
Nagaraj G. Cholli
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Virtual Machines ◽  
Cloud Service ◽  
Software Systems ◽  
System Failure ◽  
Dynamic Nature ◽  
Software Aging ◽  
Software Rejuvenation ◽  
The Impact

Cloud Computing is the environment in which several virtual machines (VM) run concurrently on physical machines. The cloud computing infrastructure hosts multiple cloud service segments that communicate with each other using the interfaces. This creates distributed computing environment. During operation, the software systems accumulate errors or garbage that leads to system failure and other hazardous consequences. This status is called software aging. Software aging happens because of memory fragmentation, resource consumption in large scale and accumulation of numerical error. Software aging degrads the performance that may result in system failure. This happens because of premature resource exhaustion. This issue cannot be determined during software testing phase because of the dynamic nature of operation. The errors that cause software aging are of special types. These errors do not disturb the software functionality but target the response time and its environment. This issue is to be resolved only during run time as it occurs because of the dynamic nature of the problem. To alleviate the impact of software aging, software rejuvenation technique is being used. Rejuvenation process reboots the system or re-initiates the softwares. This avoids faults or failure. Software rejuvenation removes accumulated error conditions, frees up deadlocks and defragments operating system resources like memory. Hence, it avoids future failures of system that may happen due to software aging. As service availability is crucial, software rejuvenation is to be carried out at defined schedules without disrupting the service. The presence of Software rejuvenation techniques can make software systems more trustworthy. Software designers are using this concept to improve the quality and reliability of the software. Software aging and rejuvenation has generated a lot of research interest in recent years. This work reviews some of the research works related to detection of software aging and identifies research gaps.

scholarly journals THE BIS-GRID ENGINE: AN ORCHESTRATION AS A SERVICE INFRASTRUCTURE

2014 ◽  
pp. 96-104
Author(s):  
André Höing ◽  
Guido Scherp ◽  
Stefan Gudenkauf
Keyword(s):  
Cloud Computing ◽  
Information System ◽  
System Integration ◽  
Cloud Service ◽  
Security Requirements ◽  
Integration Platform ◽  
Platform As A Service ◽  
Information System Integration ◽  
Cloud Technologies ◽  
Need For Information

The need for information system integration is typical for many companies including small and medium-sized enterprises (SMEs). But especially for SMEs, the costs to run a full-fledged integration platform in-house are beyond the available IT budget. This article describes the concept of Orchestration as a Service (OaaS), a specialization of the Platform as a Service (PaaS) paradigm in the Cloud (computing) world. The goal of this paradigm is to provide a workflow-based integration platform as a (Cloud) service focusing on so-called service orchestrations. We present the BIS-Grid Engine as a core middleware for an OaaS infrastructure including a discussion about how our solution addresses security requirements that are a key issue in Cloud technologies.

A Study on Cloud Storage Security Method Using Data Classification

2021 ◽  
Vol 23 (09) ◽  
pp. 1105-1121
Author(s):  
Dr. Ashish Kumar Tamrakar ◽  
◽  
Dr. Abhishek Verma ◽  
Dr. Vishnu Kumar Mishra ◽  
Dr. Megha Mishra ◽  
...  
Keyword(s):  
Cloud Storage ◽  
Storage Systems ◽  
Data Classification ◽  
Data Encryption ◽  
Security Requirements ◽  
Security And Privacy ◽  
Security Level ◽  
Distributed Resources ◽  
Storage Security ◽  
Public Data

Cloud computing is a new model for providing diverse services of software and hardware. This paradigm refers to a model for enabling on-demand network access to a shared pool of configurable computing resources, that can be rapidly provisioned and released with minimal service provider interaction .It helps the organizations and individuals deploy IT resources at a reduced total cost. However, the new approaches introduced by the clouds, related to computation outsourcing, distributed resources and multi-tenancy concept, increase the security and privacy concerns and challenges. It allows users to store their data remotely and then access to them at any time from any place .Cloud storage services are used to store data in ways that are considered cost saving and easy to use. In cloud storage, data are stored on remote servers that are not physically known by the consumer. Thus, users fear from uploading their private and confidential files to cloud storage due to security concerns. The usual solution to secure data is data encryption, which makes cloud users more satisfied when using cloud storage to store their data. Motivated by the above facts; we have proposed a solution to undertake the problem of cloud storage security. In cloud storage, there are public data that do not need any security measures, and there are sensitive data that need applying security mechanisms to keep them safe. In that context, data classification appears as the solution to this problem. The classification of data into classes, with different security requirements for each class is the best way to avoid under security and over security situation. The existing cloud storage systems use the same Journal of University of Shanghai for Science and Technology ISSN: 1007-6735 Volume 23, Issue 9, September – 2021 Page-1105 key size to encrypt all data without taking into consideration its confidentiality level. Treating the low and high confidential data with the same way and at the same security level will add unnecessary overhead and increase the processing time. In our proposal, we have combined the K-NN (K Nearest Neighbors) machine learning method and the goal programming decision-making method, to provide an efficient method for data classification. This method allows data classification according to the data owner security needs. Then, we introduce the user data to the suitable security mechanisms for each class. The use of our solution in cloud storage systems makes the data security process more flexible, besides; it increases the cloud storage system performance and decreases the needed resources, which are used to store the data.

Cloud-Based Platforms and Infrastructures

2017 ◽  
pp. 47-90
Author(s):  
Marcus Tanque
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Cloud Service ◽  
Resource Provisioning ◽  
Virtual Networks ◽  
Network Resources ◽  
Computing Services ◽  
Service Models ◽  
Cloud Computing Services ◽  
Shared Network

Cloud computing consists of three fundamental service models: infrastructure-as-a-service, platform-as-a service and software-as-a-service. The technology “cloud computing” comprises four deployment models: public cloud, private cloud, hybrid cloud and community cloud. This chapter describes the six cloud service and deployment models, the association each of these services and models have with physical/virtual networks. Cloud service models are designed to power storage platforms, infrastructure solutions, provisioning and virtualization. Cloud computing services are developed to support shared network resources, provisioned between physical and virtual networks. These solutions are offered to organizations and consumers as utilities, to support dynamic, static, network and database provisioning processes. Vendors offer these resources to support day-to-day resource provisioning amid physical and virtual machines.

scholarly journals eHealth Cloud Security Challenges: A Survey

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Yazan Al-Issa ◽  
Mohammad Ashraf Ottom ◽  
Ahmed Tamrawi
Keyword(s):  
Cloud Computing ◽  
Resource Sharing ◽  
Energy Savings ◽  
Service Providers ◽  
Healthcare Providers ◽  
Cloud Service ◽  
Cloud Security ◽  
Security And Privacy ◽  
Healthcare Industry ◽  
Sensitive Data

Cloud computing is a promising technology that is expected to transform the healthcare industry. Cloud computing has many benefits like flexibility, cost and energy savings, resource sharing, and fast deployment. In this paper, we study the use of cloud computing in the healthcare industry and different cloud security and privacy challenges. The centralization of data on the cloud raises many security and privacy concerns for individuals and healthcare providers. This centralization of data (1) provides attackers with one-stop honey-pot to steal data and intercept data in-motion and (2) moves data ownership to the cloud service providers; therefore, the individuals and healthcare providers lose control over sensitive data. As a result, security, privacy, efficiency, and scalability concerns are hindering the wide adoption of the cloud technology. In this work, we found that the state-of-the art solutions address only a subset of those concerns. Thus, there is an immediate need for a holistic solution that balances all the contradicting requirements.

scholarly journals A Strong Law for the Rate of Growth of Long Latency Periods in a Cloud Computing Service

2012 ◽  
Vol 44 (4) ◽  
pp. 995-1017 ◽  
Author(s):  
Souvik Ghosh ◽  
Soumyadip Ghosh
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Service Providers ◽  
Large Deviation ◽  
Cloud Service ◽  
Strong Law ◽  
Customer Expectations ◽  
Service Guarantees ◽  
Long Latency ◽  
Cloud Computing Service

Cloud-computing shares a common pool of resources across customers at a scale that is orders of magnitude larger than traditional multiuser systems. Constituent physical compute servers are allocated multiple ‘virtual machines' (VMs) to serve simultaneously. Each VM user should ideally be unaffected by others’ demand. Naturally, this environment produces new challenges for the service providers in meeting customer expectations while extracting an efficient utilization from server resources. We study a new cloud service metric that measures prolonged latency or delay suffered by customers. We model the workload process of a cloud server and analyze the process as the customer population grows. The capacity required to ensure that the average workload does not exceed a threshold over long segments is characterized. This can be used by cloud operators to provide service guarantees on avoiding long durations of latency. As part of the analysis, we provide a uniform large deviation principle for collections of random variables that is of independent interest.

scholarly journals Hybrid Secure Model for Securing Data in The Cloud Computing System by Combining RSA, AES and CP-ABE: نموذج هجين آمن لحماية البيانات في الحوسبة السحابية بدمج RSA وAES وCP-ABE

2021 ◽  
Vol 5 (4) ◽  
pp. 80-59
Author(s):  
Zakria Mahrousa, Mahmoud Rahhal, Nairouz Alzin Zakria Mahrousa, Mahmoud Rahhal, Nairouz Alzin
Keyword(s):  
Health Care ◽  
Cloud Computing ◽  
Access Control ◽  
Healthcare System ◽  
Service Providers ◽  
Security Requirements ◽  
Security And Privacy ◽  
Rsa Algorithm ◽  
Aes Algorithm ◽  
Cloud Computing System

The cloud healthcare system represents an important application for cloud computing, as it uses the cloud for the operations of storing patient medical data and sharing it between health care service providers and patients, making the security and privacy of e-health system data the main concern of researchers. This paper presents an integrated secure model for the healthcare system in cloud computing that achieves the security and confidentiality of data transferred through cloud computing, by combining the two algorithms AES and RSA with the access control algorithm CP-ABE in order to use the advantages of each of them, where the encryption process is done by a proposed algorithm which is based on the RSA algorithm, the XOR parameter, and the AES algorithm; the secrecy of the AES algorithm has been increased by generating a dynamic key, and the confidentiality of this key has been secured with two encryption levels, the first level using the CP-ABE algorithm and the second level using the RSA algorithm. The proposed model is characterized by meeting the requirements of access control, authentication, and verification for both the transmitter and the receiver, and the results of the application of this model proved its ability to meet the security requirements of the health care system in cloud computing with the lowest possible implementation time, as the execution times were at the transmitter's end (43.2, 43.83, 45.11, 48. 23, 50.77, 52.16, 57.95, 63.2, and 63.35)ms for variable file sizes (37, 50, 100, 150, 200, 256, 512, 1000, and 1024)KB, respectively. The results also showed its superiority in terms of security requirements in cloud computing and the necessary implementation times on studied reference models.

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