Threat Modeling for Digital Twins
• Proper identification of assets when it comes to availability / security / other systems-ility to not related to a single component, but in the relationship of components
• Consistency of the assets.
The capabilities list from van Schalkwyk’ s user guide [ 4 ] may provide the base for asset identification, addressing the listed issues. The capabilities of digital twins, can be broken into six key high-level categories:
• Data services
• Integration
• Intelligence
• User experience( UX)
• Management and
• Trustworthiness.
Each of these categories further expands into 62 discrete top-level capabilities of a digital twin ecosystem.
The proposed approach for asset identification is to verbally describe the system and decompose it into the presented capabilities from the list. This helps not to duplicate assets and not to miss anything in their listing.
Example
By using this approach, the following capabilities from [ 4 ] are listed for the FleetTwin case study:
1. Specific devices( ECUs) are used for data gathering from each vehicle, these devices and connected sensors are critical for the entire system so they are under monitoring: o Device Security o Device Management o Event logging o System monitoring
2. Telematics devices continuously send data to the cloud via secured network connection: o Data Acquisition & Ingestion o Data Streaming o Data Encryption
3. Raw data is cleaned, structured, and stored in databases: o Data Transformation o Data Contextualization o Batch Processing o Data Aggregation
4. Digital twin engine pulls the data to update virtual models in near real-time.
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