Modeling and verifying a resource allocation algorithm for secure service migration for commercial cloud systems
Karthick, Gayathri ORCID: https://orcid.org/0000-0003-1228-7099, Mapp, Glenford E.
ORCID: https://orcid.org/0000-0002-0539-5852, Kammueller, Florian
ORCID: https://orcid.org/0000-0001-5839-5488 and Aiash, Mahdi
ORCID: https://orcid.org/0000-0002-3984-6244
(2022)
Modeling and verifying a resource allocation algorithm for secure service migration for commercial cloud systems.
Computational Intelligence, 38
(3)
.
pp. 811-828.
ISSN 0824-7935
[Article]
(doi:10.1111/coin.12421)
Abstract
Cloud computing is the delivery of on‐demand computing resources. It shares the resources or provides vir‐utilization that enables single user to access various Cloud services such as CPU, memory, storage devices, network, and so on. However, more commercial cloud services offered by several cloud service providers (CSPs) are available in the market place. Most CSPs must, therefore, deal with the dynamic resource allocation where the mobile services are migrating from one cloud to another cloud environment to provide heterogeneous resources based on user needs. There is still a lack of heuristics that are able to check requested resources and available resources to allocate and deallocate before it begins the secure service migration. We proposed a resource allocation security protocol that allows resources to be allocated and migrated efficiently in a secure service migration between cloud infrastructures. Furthermore, formal methods can be used for protocols to verify the desired properties, detecting attacks and producing accurate outcomes. This article presents formal modeling and verification of this abstract protocol using ProVerif cryptographic tool to validate the security properties such as secrecy of resources, authentication from both parties and key exchange in order to securely migrate resources in commercial cloud environments.
Item Type: | Article |
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Additional Information: | Volume38, Issue3 - Special Issue: AI and Machine Learning for Smart Cities - Part 2. Intelligent Optimization Methods and their Applications - Part 2 |
Keywords (uncontrolled): | cloud systems, formal methods, mobile services, QoS, resource allocation, security protocols |
Research Areas: | A. > School of Science and Technology > Computer and Communications Engineering |
Item ID: | 32160 |
Useful Links: | |
Depositing User: | Jisc Publications Router |
Date Deposited: | 22 Feb 2021 09:19 |
Last Modified: | 30 Jun 2022 14:46 |
URI: | https://eprints.mdx.ac.uk/id/eprint/32160 |
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