Practical causal models for cyber-physical systems

Amjad Ibrahim, Severin Kacianka, Alexander Pretschner, Charles Hartsell, Gabor Karsai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

Abstract

Unlike faults in classical systems, faults in Cyber-Physical Systems will often be caused by the system’s interaction with its physical environment and social context, rendering these faults harder to diagnose. To complicate matters further, knowledge about the behavior and failure modes of a system are often collected in different models. We show how three of those models, namely attack trees, fault trees, and timed failure propagation graphs can be converted into Halpern-Pearl causal models, combined into a single holistic causal model, and analyzed with actual causality reasoning to detect and explain unwanted events. Halpern-Pearl models have several advantages over their source models, particularly that they allow for modeling preemption, consider the non-occurrence of events, and can incorporate additional domain knowledge. Furthermore, such holistic models allow for analysis across model boundaries, enabling detection and explanation of events that are beyond a single model. Our contribution here delineates a semi-automatic process to (1) convert different models into Halpern-Pearl causal models, (2) combine these models into a single holistic model, and (3) reason about system failures. We illustrate our approach with the help of an Unmanned Aerial Vehicle case study.

Original languageEnglish
Title of host publicationNASA Formal Methods - 11th International Symposium, NFM 2019, Proceedings
EditorsKristin Yvonne Rozier, Julia M. Badger
PublisherSpringer Verlag
Pages211-227
Number of pages17
ISBN (Print)9783030206512
DOIs
StatePublished - 2019
Event11th International Symposium on NASA Formal Methods, NFM 2019 - Houston, United States
Duration: 7 May 20199 May 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11460 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Symposium on NASA Formal Methods, NFM 2019
Country/TerritoryUnited States
CityHouston
Period7/05/199/05/19

Keywords

  • Causal reasoning
  • Cyber-Physical Systems
  • Halpern-Pearl Causality
  • Timed Failure Propagation Graphs

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