Title
QuantiC: Distance Metrics for Evaluating Multi-Tenancy Threats in Public Cloud
Abstract
As a cornerstone of cloud computing, multi-tenancy brings not only the benefit of resource sharing but also additional security implications. To achieve an optimal trade-off between security and resource sharing, cloud providers are obliged to evaluate the potential threats related to multi-tenancy. However, quantitative approaches for evaluating those threats are largely missing in existing works. In this paper, we propose a set of multi-level distance metrics that quantify the proximity of tenants' virtual resources inside a cloud. Those metrics are defined based on the configuration and deployment in a cloud, such that a cloud provider may apply them to evaluate the risk related to potential multi-tenancy attacks. We conduct case studies and experiments on both real and fictitious clouds. The obtained results show the effectiveness and applicability of our metrics. We further implement our metrics in OpenStack and show how they can be applied for distance auditing.
Year
DOI
Venue
2018
10.1109/CloudCom2018.2018.00042
2018 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)
Keywords
Field
DocType
Multi-Tenancy, Security Metrics, SDN-Based Cloud, OpenFlow
Software deployment,Audit,Computer science,Computer security,Multitenancy,Cloud provider,OpenFlow,Shared resource,Cornerstone,Distributed computing,Cloud computing
Conference
ISSN
ISBN
Citations 
2330-2194
978-1-5386-7900-5
0
PageRank 
References 
Authors
0.34
11
7
Name
Order
Citations
PageRank
Taous Madi1935.51
Mengyuan Zhang2362.81
Yosr Jarraya317314.52
Amir Alimohammadifar471.49
Makan Pourzandi521628.31
Lingyu Wang61440121.43
Mourad Debbabi71467144.47