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Generation of Cyberattacks Leading to Safety Top Event Using AltaRica: an Automotive Case Study

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Théo Serru
  • Function : Author
  • PersonId : 1119084
Nga Nguyen
  • Function : Author
  • PersonId : 951107
Michel Batteux
Raphael Blaize
  • Function : Author
Laurent Sagaspe
  • Function : Author
  • PersonId : 948727
Emmanuel Arbaretier
  • Function : Author
  • PersonId : 1120677

Abstract

Cyber-Physical Systems (CPS) are safety critical as they can be at risk for their users and environment. It is thus paramount to assess all risks related to their use, including the risks of cyberattacks. Indeed, malicious intruders are more and more active on such systems because of their interconnected nature. In this paper, we present a method to assess the risks of cyberattacks on CPS and their effects on safety. Thus we will show how to use the language AltaRica and the tool SimfiaNeo to model the behavior of these systems in case of cyberattacks and to generate the sequences of events leading to a safety critical state. Models based on discrete event systems like AltaRica are, however, subject to state-space explosion. To overcome this issue, we will present a new cutoff, called footprint, used to reduce the computation time and keep only relevant sequences of events. To illustrate the effectiveness of our work, we will use an automotive case study as an illustration.
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Dates and versions

hal-03814648 , version 1 (09-12-2022)

Identifiers

  • HAL Id : hal-03814648 , version 1

Cite

Théo Serru, Nga Nguyen, Michel Batteux, Antoine Rauzy, Raphael Blaize, et al.. Generation of Cyberattacks Leading to Safety Top Event Using AltaRica: an Automotive Case Study. Congrès Lambda Mu 23 « Innovations et maîtrise des risques pour un avenir durable » - 23e Congrès de Maîtrise des Risques et de Sûreté de Fonctionnement, Institut pour la Maîtrise des Risques, Oct 2022, Paris-Saclay, France. ⟨hal-03814648⟩
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