Visible to the public Security Risk-Aware Resource Provisioning Scheme for Cloud Computing Infrastructures

TitleSecurity Risk-Aware Resource Provisioning Scheme for Cloud Computing Infrastructures
Publication TypeConference Paper
Year of Publication2019
AuthorsHalabi, Talal, Bellaiche, Martine
Conference Name2019 IEEE Conference on Communications and Network Security (CNS)
PublisherIEEE
ISBN Number978-1-5386-7117-7
KeywordsArtificial Bee Colony, cloud computing, cloud computing environment, cloud computing infrastructure, cloud computing technology, cloud data centers, cloud security risk-aware resource provisioning scheme, cloud service providers, compositionality, customers security requirements, evolutionary computation, genetic algorithm, InterCloud, pubcrawl, quantitative security risk evaluation approach, resource provisioning, risk management, Scalability, security metrics, security of data, security risk, security scalability
Abstract

The last decade has witnessed a growing interest in exploiting the advantages of Cloud Computing technology. However, the full migration of services and data to the Cloud is still cautious due to the lack of security assurance. Cloud Service Providers (CSPs)are urged to exert the necessary efforts to boost their reputation and improve their trustworthiness. Nevertheless, the uniform implementation of advanced security solutions across all their data centers is not the ideal solution, since customers' security requirements are usually not monolithic. In this paper, we aim at integrating the Cloud security risk into the process of resource provisioning to increase the security of Cloud data centers. First, we propose a quantitative security risk evaluation approach based on the definition of distinct security metrics and configurations adapted to the Cloud Computing environment. Then, the evaluated security risk levels are incorporated into a resource provisioning model in an InterCloud setting. Finally, we adopt two different metaheuristics approaches from the family of evolutionary computation to solve the security risk-aware resource provisioning problem. Simulations show that our model reduces the security risk within the Cloud infrastructure and demonstrate the efficiency and scalability of proposed solutions.

URLhttps://ieeexplore.ieee.org/document/8802752
DOI10.1109/CNS.2019.8802752
Citation Keyhalabi_security_2019