Towards a Digital Twin Framework for Secure and Efficient Cyber-Physical Transportation Systems
Proceedings of the 1st Workshop on Modeling and Verification for Secure and Performant Cyber-Physical Systems (MoVe4SPS ’25), pp. 1–6
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Abstract
Cyber-Physical Systems (CPS) integrating autonomous vehicles (AVs) for mixed transport of people and goods necessitate robust methodologies to ensure secure, high-performance operations. This paper proposes a Digital Twin (DT) framework for a centralized transportation network, designed to optimize performance and enhance security using feedback-driven mechanisms. Real-time data from AVs is fed into the DT to enable Model Predictive Control (MPC), optimizing efficiency while ensuring compliance with system constraints. Behavioral profiling and pattern recognition are employed to detect misuse and anomalous vehicle behavior, bolstering system security through intrusion detection. The feedback loops compare DT predictions against real-world data to preemptively mitigate threats and operational inefficiencies, offering a flexible approach to securing and improving CPS performance.
Summary
This overview is based on the published abstract; the full text is available from ACM via the DOI.
Research question
Transport networks in which autonomous vehicles (AVs) move both people and goods are cyber-physical systems with two demanding goals at once: they must operate efficiently, and they must be protected against misuse. The paper asks how a digital twin (DT) of a centrally coordinated transportation network can support both goals.
Approach and contribution
The paper proposes a DT framework built around feedback loops. Real-time data from the vehicles feeds the digital twin, which runs model predictive control (MPC) to optimise efficiency while respecting the system’s constraints. In parallel, behavioural profiling and pattern recognition detect misuse and anomalous vehicle behaviour, acting as an intrusion detection layer. By continuously comparing DT predictions with real-world observations, the framework aims to mitigate threats and operational inefficiencies before they escalate.
Why it matters
The paper outlines how a single digital twin can serve both performance optimisation and security monitoring in cyber-physical transportation systems. Later papers by the same authors study digital twins and runtime optimisation with formal guarantees, listed under related papers below.
Keywords
digital twins; cyber-physical systems; autonomous vehicles; model predictive control; intrusion detection; transportation systems
Cite
@inproceedings{brodo2025dttransport,
author = {Brodo, Luca and Scalora, Giuseppe and Henkler, Stefan},
title = {Towards a Digital Twin Framework for Secure and Efficient Cyber-Physical Transportation Systems},
booktitle = {Proceedings of the 1st Workshop on Modeling and Verification for Secure and Performant Cyber-Physical Systems},
series = {MoVe4SPS '25},
pages = {1--6},
year = {2025},
publisher = {Association for Computing Machinery},
doi = {10.1145/3735948.3736156},
url = {https://doi.org/10.1145/3735948.3736156}
}