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CBAC4C: conflict-based VM isolation control for cloud computing

delete2021-01-14
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OA
AI
M
Moses Dlamini *
J
Jan H. P. Eloff
H
Hein S. Venter
M
Mariki M. Eloff
DOI:10.1111/itor.12935delete
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摘要

摘要

En 中文
For businesses to benefit from the many opportunities of cloud computing, they must first address a number of security challenges, such as the potential leakage of confidential data to unintended third parties. An inter-VM (where VM is virtual machine) attack, also known as cross-VM attack, is one threat through which cloud-hosted confidential data could be leaked to unintended third parties. An inter-VM attack exploits vulnerabilities between co-resident guest VMs that share the same cloud infrastructure. In an attempt to stop such an attack, this paper uses the principles of logical analysis to model a solution that provides physical separation of VMs belonging to conflicting tenants based on their levels of conflict. The derived mathematical model is founded on scientific principles and implemented using four conflict-aware VM placement algorithms. The resultant algorithms consider a tenant's risk appetite and cost implications. The model offers guidance to VM placement and is validated using a proof of concept. A cloud simulation tool was used to test and evaluate the effectiveness and efficiency of the model. The findings reflect that the introduction of the proposed model introduced a time lag in the time it took to place VM instances. On top of this, it was also discovered that the number and size of the VM instances has an effect on the VM placement performance. The findings further illustrate that the conflict tolerance level of a VM has a direct impact on the time it took to place.
Keyword:
cloud computing
conflict-aware virtual machine placement
data leakage
mathematical modeling
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期刊

International Transactions in Operational Research 封面图
International Transactions in Operational Research
IF:
2.9
论文数:
1.8K
被引数:
3.7K

机构

U
university of south africa
学者数:
4.8K
论文数: 4.2K
被引数: 0
U
university of pretoria
学者数:
1.2W
论文数: 9.9K
被引数: 6
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