Information (Dec 2022)

THREATGET: Towards Automated Attack Tree Analysis for Automotive Cybersecurity

  • Sebastian Chlup,
  • Korbinian Christl,
  • Christoph Schmittner,
  • Abdelkader Magdy Shaaban,
  • Stefan Schauer,
  • Martin Latzenhofer

DOI
https://doi.org/10.3390/info14010014
Journal volume & issue
Vol. 14, no. 1
p. 14

Abstract

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The automotive domain is moving away from simple isolated vehicles to interconnected networks of heterogeneous systems forming a complex transportation infrastructure. The additional means of communication result in increased attack surfaces which can be exploited by physical as well as remote attackers if not secured thoroughly. Thus, the automotive sector is exposed to new cyber risk factors. Consequently, joint approaches targeting securing vehicles and infrastructure by identifying and mitigating potential threats for the automotive domain have been developed in several research projects. This paper builds on developments originating from these projects and correlated standards and regulations. Moreover, the extension of an existing threat modeling tool—THREATGET—with a novel automated approach toward attack propagation will be introduced. Therefore, we will conduct an analysis of a real-world example from the automotive domain. Furthermore, we will identify and analyze potential threats and discuss their accumulation to automatically generate an attack tree.

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