Explainable Cryptographic Key-Lifecycle Management via Knowledge Graphs
Keywords:
key management, knowledge graphs, graph attention networks, explainability, cryptographic lifecycleAbstract
The objective of this paper is to propose a framework for cryptographic key-lifecycle management system that employs knowledge graphs and interpretable machine learning. Unification of relationships among the key sources, usage, and rotation frequency are considered by combining keys, devices, tokens, and policy needs into a semantic network. We use policy artifacts as context anchors to train Graph Attention Networks (GATs) in this graph representation which assess the importance of rotation and harm related for following the rules.
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