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For a long time threat modeling was treated as a manual, complicated process.However modern agile development methodologies and cloud computing technologiesrequire adding automatic threat modeling approaches. This work considers twochallenges: creating a set of machine-readable data flow diagrams thatrepresent real cloud based applications; and usage domain specific knowledgefor automatic analysis of the security aspects of such applications. The set of180 semantic diagrams (ontologies and knowledge graphs) is created based oncloud configurations (Docker Compose); the set includes a manual taxonomy thatallows to define the design and functional aspects of the web based and dataprocessing applications; the set can be used for various research in the threatmodeling field. This work also evaluates how ontologies and knowledge graphscan be used to automatically recognize patterns (mapped to security threats) indiagrams. A pattern represents features of a diagram in form of a request to aknowledge base, what enables its recognition in a semantic representation of adiagram. In an experiment four groups of the patterns are created (webapplications, data processing, network, and docker specific), and the diagramsare examined by the patterns. Automatic results, received for the webapplications and data processing patterns, are compared with the manualtaxonomy in order to study challenges of automatic threat modeling.

A set of semantic data flow diagrams and its security analysis based on ontologies and knowledge graphs