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Diagnosability of Attack Trees

  • 2026
  • OriginalPaper
  • Chapter
Published in:
Authors
Damas Gruska
Aliyu Tanko Ali
Martin Leucker
Published in
Advancing Innovative Cybersecurity Solutions and Approaches to Protect Digital Ecosystems
Publisher
Springer Nature Switzerland

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Abstract

This chapter delves into the complexities of diagnosing attacks using attack trees (ATs) under conditions of partial observability. It introduces an extended AT model that incorporates time and cost constraints, enabling a more nuanced analysis of attack scenarios. The text explores how defenders can reconstruct attack sequences from incomplete observations, addressing the challenges posed by multiple attack paths that may fit the same partial evidence. The chapter also discusses the relationship between diagnosability and initial-state opacity, highlighting the trade-offs involved in enhancing defensive capabilities while preserving critical secrecy. Practical applications and examples are provided to illustrate the concepts, including the use of the TAPAAL software tool for modeling and analysis. The chapter concludes with a discussion on the implications of diagnosability for system security and future research directions.
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This summary of the content was generated with the help of AI.

Work funded by the EU NextGenerationEU through the Recovery and Resilience Plan for Slovakia under the project No. 09I03-03-V04-00095.

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previous chapter Enhancing Digital Wallet Security: A Systematic Comparison of Passwordless and Risk-Based Authentication Approaches
Title
Diagnosability of Attack Trees
Authors
Damas Gruska
Aliyu Tanko Ali
Martin Leucker
Copyright Year
2026
Book
Advancing Innovative Cybersecurity Solutions and Approaches to Protect Digital Ecosystems

Print ISBN: 978-3-032-13074-7

Electronic ISBN: 978-3-032-13075-4

Copyright Year: 2026

DOI
https://doi.org/10.1007/978-3-032-13075-4_17
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