SEAL-DT: An End-to-End Security Engineering and Assurance Framework for Cross-Domain Digital Twins

Abstract

Cyber-physical systems connect physical processes, software, networks and organizations. Securing them requires a clear account of what happened, what was observed, which actions were authorized and what evidence supports each decision. Digital Twin (DT) descriptions often fail to explain how these elements stay consistent, blur the distinction between physical events and uncertain observations, or detach simulation results from their requirements and assumptions. This paper presents SEAL-DT (Security Engineering and Assurance Lifecycle for Digital Twins), a structured approach to building and evaluating secure DTs. It brings entity definitions, process models, deterministic simulations, data contracts, evidence records, automated tests and reproducible results into one connected model. The main contribution is an end-to-end DT security framework, spanning scenario definition, entity/process modelling, simulation, security decision logic, evidence handling, validation and reproducible reporting. Security decisions and simulation results thus trace back to their data, assumptions and requirements. A DT is more than a copy of system state: it states what it can observe, how accurate and current its information is, where it came from and which decisions it may support. We demonstrate SEAL-DT in five scenarios: Car2X protection, passive IoT-device detection, an industrial control surrogate, lawful acquisition in a smart home, and medical-IoT monitoring that preserves continuity of care. Each includes formal models, deterministic and negative experiments, uncertainty analyses, schema-valid fixtures, technical reports and verified manifests, testing multiple configurations under normal and adverse conditions. Results show that the framework supports consistent model construction, traceable execution and comparable internal validation, and that security findings link to observable evidence.