CloudSafe: A Tool for an Automated Security Analysis for Cloud Computing
March 11, 2019 Β· Declared Dead Β· π 2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)
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Authors
Seoungmo An, Taehoon Eom, Jong Sou Park, Jin B. Hong, Armstrong Nhlabatsi, Noora Fetais, Khaled M. Khan, Dong Seong Kim
arXiv ID
1903.04271
Category
cs.CR: Cryptography & Security
Citations
17
Venue
2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)
Last Checked
4 months ago
Abstract
Cloud computing has been adopted widely, providing on-demand computing resources to improve perfornance and reduce the operational costs. However, these new functionalities also bring new ways to exploit the cloud computing environment. To assess the security of the cloud, graphical security models can be used, such as Attack Graphs and Attack Trees. However, existing models do not consider all types of threats, and also automating the security assessment functions are difficult. In this paper, we propose a new security assessment tool for the cloud named CloudSafe, an automated security assessment for the cloud. The CloudSafe tool collates various tools and frameworks to automate the security assessment process. To demonstrate the applicability of the CloudSafe, we conducted security assessment in Amazon AWS, where our experimental results showed that we can effectively gather security information of the cloud and carry out security assessment to produce security reports. Users and cloud service providers can use the security report generated by the CloudSafe to understand the security posture of the cloud being used/provided.
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