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Integrating Adversary Models and Intrusion Detection Systems for In-vehicle Networks in CANoe

  • Camil JichiciEmail author
  • Bogdan Groza
  • Pal-Stefan Murvay
Conference paper
  • 31 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12001)

Abstract

In-vehicle buses and the Controller Area Network (CAN) in particular have been shown to be vulnerable to adversarial actions. We embed adversary models and intrusion detection systems (IDS) inside a CANoe based application. Based on real-world CAN traces collected from several vehicles we build attack traces that are subject to intrusion detection algorithms. We also take benefit from existing machine-learning support in MATLAB that is ported via C++ code in CANoe in order to integrate intrusion detection functionality. A unified framework for attacks and intrusion detection has the benefit of providing a testbed for various intrusion detection algorithms. CANoe integration makes the use of these functionalities ready for realistic testing as CANoe is an industry-standard tool in the automotive domain.

Keywords

CAN bus Vehicle security Intrusion detection 

Notes

Acknowledgement

This work was supported by a grant of the Romanian Ministry of Research and Innovation, CNCS - UEFISCDI, project number PN-III-P1-1.1-PD-2016-1198, within PNCDI III.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Camil Jichici
    • 1
    Email author
  • Bogdan Groza
    • 1
  • Pal-Stefan Murvay
    • 1
  1. 1.Faculty of Automatics and ComputersPolitehnica University of TimisoaraTimişoaraRomania

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