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KACEM_HAKIM_31932301_2025.pdf
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- The increasing software complexity of modern vehicles, particularly the use of networked Electronic Control Units (ECUs) over the Controller Area Network (CAN) bus, has expanded the automotive cybersecurity attack surface. Despite this, researchers often lack accessible and reproducible environments that accurately reflect ECU interactions and vehicle behavior under cyber-physical attack scenarios. This thesis introduces CANvas, an open-source simulation platform designed to fill this gap. CANvas models eight core ECUs—covering powertrain, stability, steering, and body control—each implemented as an independent thread with realistic CAN timing and communication. It features a modular attack framework for evaluating scenarios such as spoofed sensor inputs and unauthorized actuator commands. A graphical dashboard provides live visualization of internal vehicle states, and structured export capabilities enable reproducibility and offline analysis. While limited in physical dynamics and ECU diversity, CANvas serves as a practical foundation for controlled experimentation in automotive cybersecurity research.