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Automotive Security Analyzer for Exploitability Risks

An Automated and Attack Graph-Based Evaluation of On-Board Networks

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  • © 2024

Overview

Authors:
  1. Martin Salfer

    1. München, Germany

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About this book

Our lives depend on automotive cybersecurity, protecting us inside and near vehicles. If vehicles go rogue, they can operate against the driver’s will and potentially drive off a cliff or into a crowd. The “Automotive Security Analyzer for Exploitability Risks” (AutoSAlfER) evaluates the exploitability risks of automotive on-board networks by attack graphs. AutoSAlfER’s Multi-Path Attack Graph algorithm is 40 to 200 times smaller in RAM and 200 to 5 000 times faster than a comparable implementation using Bayesian networks, and the Single-Path Attack Graph algorithm constructs the most reasonable attack path per asset with a computational, asymptotic complexity of only O(n * log(n)), instead of O(n²). AutoSAlfER runs on a self-written graph database, heuristics, pruning, and homogenized Gaussian distributions and boosts people’s productivity for a more sustainable and secure automotive on-board network. Ultimately, we enjoy more safety and security in and around autonomous, connected, electrified, and shared vehicles.





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Table of contents (6 chapters)

  1. Front Matter

    Pages i-xxv
    Download chapter PDF

  2. Introduction

    • Martin Salfer
    Pages 1-14

  3. Basics and Related Work

    • Martin Salfer
    Pages 15-86

  4. System Model, Attacker Profile, Exploit Model, Attack Graphs and Exploitability Quantification

    • Martin Salfer
    Pages 87-129

  5. Single-Path Attack Graph Algorithm

    • Martin Salfer
    Pages 131-155

  6. Multi-Path Attack Graph Algorithm

    • Martin Salfer
    Pages 157-207

  7. Conclusion

    • Martin Salfer
    Pages 209-212

  8. Back Matter

    Pages 213-243
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Authors and Affiliations

  • München, Germany

    Martin Salfer

About the author

Dr. Martin Salfer is an IT security researcher at TUM and a tech lead at an automaker. He earned his Ph.D. in IT Security from TUM, completed his M.Sc. with honours in Software Engineering at UniA/LMU/TUM, and obtained his B.Sc. in Computer Science from HM, with a study abroad at KPU in Vancouver, Canada, and ESIEA in Paris, France, and a research visit at NII in Tokyo, Japan. He is the lead author of 28 publications, including five IT security patents.

Bibliographic Information

  • Book Title: Automotive Security Analyzer for Exploitability Risks

  • Book Subtitle: An Automated and Attack Graph-Based Evaluation of On-Board Networks

  • Authors: Martin Salfer

  • DOI: https://doi.org/10.1007/978-3-658-43506-6

  • Publisher: Springer Vieweg Wiesbaden

  • eBook Packages: Computer Science and Engineering (German Language)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2024

  • Softcover ISBN: 978-3-658-43505-9Published: 16 March 2024

  • eBook ISBN: 978-3-658-43506-6Published: 15 March 2024

  • Edition Number: 1

  • Number of Pages: XXV, 243

  • Number of Illustrations: 10 b/w illustrations, 48 illustrations in colour

  • Topics: Circuits and Systems, Automotive Engineering

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