CPS context hierarchy models                                                                 

  WP leader: Robert Edwald, NORCE

False positives and alarms result from the ambiguity of the data. In general, the ambiguity can be resolved by taking into account the context in which the IDS data was acquired. It is usually useful to model the context into a hierarchy and using the most specific applicable context to aid tie-breaking (resolve ambiguities), thereby helping avoid false positives. WP1 will extend the Purdue model for IR4.0 and take the context of the CPS operations to be combined with the IDS data. We build upon the semantic models of the operation from the DDHub project for a semantic drilling data model.

Tasks: 

• A1.1: Literature study related to Purdue model and other relevant functional models and methods for describing structure and communication within Cyber Physical System (CPS).
• A1.2: Develop a tailored version of the Purdue model for CPS for Power grid and Petroleum. It is important to clearly represent the digital and physical parts with their respective subsystems, relations, dependencies, and interdependencies. Relevant methods: Petri-net and DDHub for structuring of CPS and process.
• A1.3: Implement and test the tailored Purdue model on the case study CPSs in the existing test laboratories. DDHub is already integrated in OpenLab drilling HIL facilities [20], while studies on infrastructure have previously been performed using Petri-net.