A Graph Neural Network-based Security Posture-aware Cloud Service Provider Selection for Multi-cloud

When bidirectional, data-intensive, scientific applications move through multiple cloud environments, the posture requirements change during transit. Security is crucial in this scenario as the applications and as well as infrastructure providers demand it. Previous studies were based on sub-optimal heuristics, and machine learning with no consideration for the bidirectional nature of the data workflows. This limitation is addressed in this work by adopting the graph structure and predicting cloud providers based on the specifications. GraphSAGE performed well with an AUC of 0.94 while having a trade-off between performance and cost. The research outcomes highlight the applicability of graph-based solutions to security-aware cloud service provider selection for bidirectional multi-cloud data workflows.