A Systematic Approach to Automotive Security

Ebrahimi Masoud (Speaker), Stefan Marksteiner, Dejan Nickovic, Roderick Bloem, David Schögler, Philipp Eisner, Samuel Sprung, Thomas Schober, Sebastian Chlup, Christoph Schmittner, Sandra König

Research output: Chapter in Book or Conference ProceedingsConference Proceedings with Oral Presentationpeer-review


We propose a holistic methodology for designing automotive systems that consider security a central concern at every design stage. During the concept design, we model the system architecture and define the security attributes of its components. We perform threat analysis on the system model to identify structural security issues. From that analysis, we derive attack trees that define recipes describing steps to successfully attack the system’s assets and propose threat prevention measures. The attack tree allows us to derive a verification and validation (V &V) plan, which prioritizes the testing effort. In particular, we advocate using learning for testing approaches for the black-box components. It consists of inferring a finite state model of the black-box component from its execution traces. This model can then be used to generate new relevant tests, model check it against requirements, and compare two different implementations of the same protocol. We illustrate the methodology with an automotive infotainment system example. Using the advocated approach, we could also document unexpected and potentially critical behavior in our example systems.
Original languageEnglish
Title of host publicationInternational Symposium on Formal Methods
EditorsMarscha Chechik, Joost-Pieter Katoen, Martin Leucker
Number of pages11
Publication statusPublished - 3 Mar 2023
Event25th International Symposium FM 2023 - Lübeck, Lübeck, Germany
Duration: 6 Mar 202310 Mar 2023

Publication series

NameFM: International Symposium on Formal Methods


Conference25th International Symposium FM 2023

Research Field

  • Dependable Systems Engineering


  • Cybersecurity
  • Testing
  • Automotive
  • Threats


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