Abstract
Continuous certification of cloud services requires a high degree of automation in collecting and evaluating evidences. Prior approaches to this topic are often specific to a cloud provider or a certain certification catalog. This makes it costly and complex to achieve conformance to multiple certification schemes and covering multi-cloud solutions. In this paper, we present a novel approach to continuous certification which is scheme- and vendor-independent. Leveraging an ontology of cloud resources and their security features, we generalize vendor- and scheme-specific terminology into a new model of so-called semantic evidence. In combination with generalized metrics that we elicited out of requirements from the EUCS and the CCMv4, we present a framework for the collection and assessment of such semantic evidence across multiple cloud providers. This allows to conduct continuous cloud certification while achieving re-usability of metrics and evidences in multiple certification schemes. The performance benchmark of the framework's prototype implementation shows that up to 200,000 evidences can be processed in less than a minute, making it suitable for short time intervals used in continuous certification.
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CITATION STYLE
Banse, C., Kunz, I., Haas, N., & Schneider, A. (2023). A Semantic Evidence-based Approach to Continuous Cloud Service Certification. In Proceedings of the ACM Symposium on Applied Computing (pp. 24–33). Association for Computing Machinery. https://doi.org/10.1145/3555776.3577600
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