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Toward Automated Security Analysis and Enforcement for Cloud Computing Using Graphical Models for Security

delete2022-01-01
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OA
AI
S
Seongmo An *
A
Asher Leung
J
Jin B. Hong
T
Taehoon Eom
J
Jong Sou Park
DOI:10.1109/ACCESS.2022.3190545delete
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Abstract

Abstract

En 中文
Cloud computing has become widely adopted by businesses for hosting applications with improved performance at a fraction of the operational costs and complexity. The rise of cloud applications has been coupled with an increase in security threat vectors and vulnerabilities. In this paper, we propose a new security assessment and enforcement tool for the cloud named CloudSafe, which provides an automated security assessment and enforce best security control for the cloud by collating various security tools. To demonstrate the applicability and usability of CloudSafe, we implemented CloudSafe and conducted security assessment in Amazon AWS. Also, we analyzed four different security countermeasure options in depth; Vulnerability Patching, Virtual Patching, Network Hardening and Moving Target Defence. Virtual Patching, Network Hardening and Moving Target Defence were determined to be feasible with regards to deployment implementation for the project. Proof of concepts were developed demonstrating the effectiveness of each feasible countermeasure option. These results indicate that the proposed tool CloudSafe is effective and efficient in helping security administrators to select optimal countermeasures to secure their cloud by conducting an in-depth security assessment.
Keywords:
Security
Cloud computing
Databases
Costs
Optimization
Cloud computing security
Automation
Cloud computing
cloud security
graphical security models
security assessment

Journal

IEEE Access cover
IEEE Access
IF:
3.6
Papers:
9.8W
Citations:
29.4W

Organization

U
University of Western Australia
Scholars:
2.9W
Papers: 3.0W
Citations: 46
K
Korea Aerospace University
Scholars:
1.0K
Papers: 1.0K
Citations: 513
U
University of Queensland
Scholars:
5.0W
Papers: 5.1W
Citations: 9.2W
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