TY - GEN
T1 - A Graph Neural Network-based Security Posture-aware Cloud Service Provider Selection for Multi-cloud
AU - Wijenayake, D. S.
AU - Henna, Shagufta
AU - Farrelly, William
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - Bidirectional data workflows
KW - Cloud security posture management
KW - Graph neural networks
KW - Network function virtualization
UR - https://www.scopus.com/pages/publications/85189932455
U2 - 10.1109/AICS60730.2023.10470882
DO - 10.1109/AICS60730.2023.10470882
M3 - Conference contribution
AN - SCOPUS:85189932455
T3 - 2023 31st Irish Conference on Artificial Intelligence and Cognitive Science, AICS 2023
BT - 2023 31st Irish Conference on Artificial Intelligence and Cognitive Science, AICS 2023
PB - IEEE
T2 - 31st Irish Conference on Artificial Intelligence and Cognitive Science, AICS 2023
Y2 - 7 December 2023 through 8 December 2023
ER -