Towards a Domain-Agnostic Knowledge Graph-As-A-Service Infrastructure for Active Cyber Defense with Intelligent Agents

Active cyber defense mechanisms are necessary to perform automated, and even autonomous operations using intelligent agents that defend against modern/sophisticated AI-inspired cyber threats (e.g., ransomware, cryptojacking, deep-fakes). These intelligent agents need to rely on deep learning using mature knowledge and should have the ability to apply this knowledge in a situational and timely manner for a given AI-inspired cyber threat. In this paper, we describe a 'domain-Agnostic knowledge graph-As-A-service' infrastructure that can support the ability to create/store domain-specific knowledge graphs for intelligent agent Apps to deploy active cyber defense solutions defending real-world applications impacted by AI-inspired cyber threats. Specifically, we present a reference architecture, describe graph infrastructure tools, and intuitive user interfaces required to construct and maintain large-scale knowledge graphs for the use in knowledge curation, inference, and interaction, across multiple domains (e.g., healthcare, power grids, manufacturing). Moreover, we present a case study to demonstrate how to configure custom sets of knowledge curation pipelines using custom data importers and semantic extract, transform, and load scripts for active cyber defense in a power grid system. Additionally, we show fast querying methods to reach decisions regarding cyberattack detection to deploy pertinent defense to outsmart adversaries.