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CARACAS: vehiCular ArchitectuRe for detAiled Can Attacks Simulation

Sadek Misto Kirdi, Nicola Scarano, Franco Oberti, Luca Mannella, Stefano Di Carlo, Alessandro Savino

TL;DR

This work tackles the lack of accessible, reproducible CAN attack datasets by introducing CARACAS, a modular Simulink/Simscape framework for BEV dynamics, CAN bus modeling, and attack injection. It generates synthetic normal and malicious CAN messages in two driving scenarios, enabling direct observation of torque-control attack effects on vehicle operation. Key contributions include integrating a BEV model with a CAN-based attack injector via CANdb++ and a signal-builder-based attack generator, and releasing open-source code. Results demonstrate that injecting a braking torque of $-15~\mathrm{Nm}$ during $t \in [160,240]$ s produces observable deviations in torque and velocity, validating CARACAS as a framework for IDS data generation.

Abstract

Modern vehicles are increasingly vulnerable to attacks that exploit network infrastructures, particularly the Controller Area Network (CAN) networks. To effectively counter such threats using contemporary tools like Intrusion Detection Systems (IDSs) based on data analysis and classification, large datasets of CAN messages become imperative. This paper delves into the feasibility of generating synthetic datasets by harnessing the modeling capabilities of simulation frameworks such as Simulink coupled with a robust representation of attack models to present CARACAS, a vehicular model, including component control via CAN messages and attack injection capabilities. CARACAS showcases the efficacy of this methodology, including a Battery Electric Vehicle (BEV) model, and focuses on attacks targeting torque control in two distinct scenarios.

CARACAS: vehiCular ArchitectuRe for detAiled Can Attacks Simulation

TL;DR

This work tackles the lack of accessible, reproducible CAN attack datasets by introducing CARACAS, a modular Simulink/Simscape framework for BEV dynamics, CAN bus modeling, and attack injection. It generates synthetic normal and malicious CAN messages in two driving scenarios, enabling direct observation of torque-control attack effects on vehicle operation. Key contributions include integrating a BEV model with a CAN-based attack injector via CANdb++ and a signal-builder-based attack generator, and releasing open-source code. Results demonstrate that injecting a braking torque of during s produces observable deviations in torque and velocity, validating CARACAS as a framework for IDS data generation.

Abstract

Modern vehicles are increasingly vulnerable to attacks that exploit network infrastructures, particularly the Controller Area Network (CAN) networks. To effectively counter such threats using contemporary tools like Intrusion Detection Systems (IDSs) based on data analysis and classification, large datasets of CAN messages become imperative. This paper delves into the feasibility of generating synthetic datasets by harnessing the modeling capabilities of simulation frameworks such as Simulink coupled with a robust representation of attack models to present CARACAS, a vehicular model, including component control via CAN messages and attack injection capabilities. CARACAS showcases the efficacy of this methodology, including a Battery Electric Vehicle (BEV) model, and focuses on attacks targeting torque control in two distinct scenarios.
Paper Structure (10 sections, 8 figures)

This paper contains 10 sections, 8 figures.

Table of Contents

  1. Introduction
  2. Related Works
  3. Proposed Approach
  4. BEV Dynamic model
  5. CAN bus model integration
  6. CAN Attack Injection simulator
  7. Results
  8. Extra Urban Driving Cycle
  9. Cruise Mode
  10. Conclusion

Figures (8)

  • Figure 1: Full Simulink model.
  • Figure 2: Torque request schema through .
  • Figure 3: Torque attack injector integration into the model.
  • Figure 4: Step signal injected to simulate a braking torque. Simulation time in seconds [s] on the x-axis and torque in Newton meters [Nm] on the y-axis.
  • Figure 5: Torque without any attack vs Torque with the attack while the vehicle is in Extra Urban Driving Cycle.
  • ...and 3 more figures