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Co-Residence Data Theft Attacks on N-Version Programming-Based Cloud Services With Task Cancelation

delete2022-01-01
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PRE
AI
G
Gregory Levitin
Liudong Xing 封面图
Liudong Xing (Liudong Xing)
Y
Yanping Xiang *
DOI:10.1109/TSMC.2020.3002930delete
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摘要

摘要

En 中文
Powered by virtualization, the cloud computing has brought good merits of cost effective and on-demand resource sharing among many users. On the other hand, cloud users face security risks from co-residence attacks when using this virtualized platform. Particularly, a malicious attacker may create side channels to steal data from a target user's virtual machine (VM) that co-resides with the attacker's VM on the same physical server. This article models a cloud service undergoing the co-residence data theft attacks. The thresholdvoting-based N-version programming (NVP) is implemented to improve the service reliability, where multiple service component versions (SCVs) are activated in parallel to perform the requested service. The final output is determined upon receiving a threshold number of identical outputs from the SCVs, immediately followed by canceling all outstanding SCVs to reduce expenses. Probabilistic models are first introduced to evaluate performance metrics of the considered service, including the data theft probability, service success probability, expected service operation time, and expected utility. Optimization problems are further solved to find the optimal number of SCVs maximizing the expected utility. Interactions among different model parameters and VM allocation policies, as well as their effects on the considered performance metrics and on the optimization solutions are studied through examples.
Keyword:
Cloud computing
data security
N-version programming (NVP)
threshold voting
virtual machine (VM)

期刊

IEEE Transactions on Cybernetics 封面图
IEEE Transactions on Cybernetics
IF:
10.5
论文数:
1.1W
被引数:
5.0W

机构

U
university of massachusetts system
学者数:
3.9W
论文数: 3.6W
被引数: 42
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