View PDF
Access through your institution
Reliability Engineering & System Safety
Volume 167, November 2017, Pages 248-254
Balancing theft and corruption threats by data partition in cloud system with independent server protection
Liudong​Xing​
a​b​
Gregory​Levitin​
c
https://doi.org/10.1016/j.ress.2017.06.006
Get rights and content
Highlights
Cloud computing systems subject to co-resident attacks are modeled.
Balance between data security (theft) and reliability (corruption) is addressed.
Optimal data partition policy problem is formulated and solved.
Influence of cloud system parameters on the partition policy is demonstrated.
Abstract
This paper models cloud computing systems subject to co-resident attacks, where an attacker can get access to a user's sensitive data through co-residence of their virtual machines on the same physical server. Both attackers’ and users’ virtual machines are distributed among cloud servers at random. It is assumed that attacker's successes in getting unauthorized access to data in different servers are independent events that can occur with a given probability. To mitigate effects of the co-resident attacks, a data protection policy based on the partition technique is applied where sensitive data are divided and distributed among multiple virtual machines in the cloud. As the information is useful only in its integrity, the attacker should get access to all of the separated data blocks to steal the information. On the other hand, corrupting any block can destroy the information and make it useless. Hence, creating more blocks can make data more difficult to steal (lower data theft probability), but easier to corrupt (higher data corruption probability). This work makes original contributions by formulating and solving constrained optimization problems to balance the data theft and data corruption probabilities. Particularly probabilistic models are first presented, which derive probabilities that an attacker can succeed in the data theft and data corruption. Further an optimal number of different data blocks (corresponding to the number of user's virtual machines) is obtained, which minimizes the data theft probability subject to meeting a data corruption probability constraint. Both fixed and uncertain numbers of attacker's virtual machines are considered. Numerical examples are presented to demonstrate influence of cloud system parameters on the optimal user's data partition policy obtained.
Previous
Next
Keywords
Cloud computing​
Co-residence attack
Data corruption, data partition
Data reliability
Data security
Data theft
Virtual machine
View full text
© 2017 Elsevier Ltd. All rights reserved.
About ScienceDirect
Remote access
Shopping cart
Advertise
Contact and support
Terms and conditions
Privacy policy
We use cookies to help provide and enhance our service and tailor content and ads. By continuing you agree to the use of cookies.
Copyright © 2021 Elsevier B.V. or its licensors or contributors. ScienceDirect ® is a registered trademark of Elsevier B.V.
ScienceDirect ® is a registered trademark of Elsevier B.V.
Journals & Books
Journals & Books
Help