Threat modeling is of increasing importance to IT security,and it is a complex and resource demanding task.The aim of automating threat modeling is to simplify model creation by using data that are already available.H...Threat modeling is of increasing importance to IT security,and it is a complex and resource demanding task.The aim of automating threat modeling is to simplify model creation by using data that are already available.However,the collected data often lack context;this can make the automated models less precise in terms of domain knowledge than those created by an expert human modeler.The lack of domain knowledge in modeling automation can be addressed with ontologies.In this paper,we introduce an ontology framework to improve automatic threat modeling.The framework is developed with conceptual modeling and validated using three different datasets:a small scale utility lab,water utility control network,and university IT environment.The framework produced successful results such as standardizing input sources,removing duplicate name entries,and grouping application software more logically.展开更多
Threat modeling is of increasing importance to IT security,and it is a complex and resource demanding task.The aim of automating threat modeling is to simplify model creation by using data that are already available.H...Threat modeling is of increasing importance to IT security,and it is a complex and resource demanding task.The aim of automating threat modeling is to simplify model creation by using data that are already available.However,the collected data often lack context;this can make the automated models less precise in terms of domain knowledge than those created by an expert human modeler.The lack of domain knowledge in modeling automation can be addressed with ontologies.In this paper,we introduce an ontology framework to improve automatic threat modeling.The framework is developed with conceptual modeling and validated using three different datasets:a small scale utility lab,water utility control network,and university IT environment.The framework produced successful results such as standardizing input sources,removing duplicate name entries,and grouping application software more logically.展开更多
基金This work has received funding from the European Unions H2020 research and innovation programme under the Grant Agreement No.832907Swedish Governmental Agency for Innovation Systems(Vinnova),the Swedish Energy Agency,SweGRIDS,and STandUP for Energy.
文摘Threat modeling is of increasing importance to IT security,and it is a complex and resource demanding task.The aim of automating threat modeling is to simplify model creation by using data that are already available.However,the collected data often lack context;this can make the automated models less precise in terms of domain knowledge than those created by an expert human modeler.The lack of domain knowledge in modeling automation can be addressed with ontologies.In this paper,we introduce an ontology framework to improve automatic threat modeling.The framework is developed with conceptual modeling and validated using three different datasets:a small scale utility lab,water utility control network,and university IT environment.The framework produced successful results such as standardizing input sources,removing duplicate name entries,and grouping application software more logically.
基金received funding from the European Unions H2020 research and innovation programme under the Grant Agreement No.832907Swedish Governmental Agency for Innovation Systems(Vinnova)the Swedish Energy Agency,SweGRIDS,and STandUP for Energy.
文摘Threat modeling is of increasing importance to IT security,and it is a complex and resource demanding task.The aim of automating threat modeling is to simplify model creation by using data that are already available.However,the collected data often lack context;this can make the automated models less precise in terms of domain knowledge than those created by an expert human modeler.The lack of domain knowledge in modeling automation can be addressed with ontologies.In this paper,we introduce an ontology framework to improve automatic threat modeling.The framework is developed with conceptual modeling and validated using three different datasets:a small scale utility lab,water utility control network,and university IT environment.The framework produced successful results such as standardizing input sources,removing duplicate name entries,and grouping application software more logically.
