Parametric Analyses of Attack-fault Tree

• Autorzy: André Étienne , Lime Didier , Ramparison Mathias , Stoelinga Mariëlle

Identyfikatory

DOI

10.3233/FI-2021-2066

• Języki publikacji: EN

Abstrakty

EN

Risk assessment of cyber-physical systems, such as power plants, connected devices and IT-infrastructures has always been challenging: safety (i. e., absence of unintentional failures) and security (i. e., no disruptions due to attackers) are conditions that must be guaranteed. One of the traditional tools used to consider these problems is attack trees, a tree-based formalism inspired by fault trees, a well-known formalism used in safety engineering. In this paper we define and implement the translation of attack-fault trees (AFTs) to a new extension of timed automata, called parametric weighted timed automata. This allows us to parameterize constants such as time and discrete costs in an AFT and then, using the model-checker IMITATOR, to compute the set of parameter values such that a successful attack is possible. Moreover, we add the possibility to define counter-measures. Using the different sets of parameter values computed, different attack and fault scenarios can be deduced depending on the budget, time or computation power of the attacker, providing helpful data to select the most efficient counter-measure.

Słowa kluczowe

EN

security; attack-fault trees; parametric timed automata; IMITATOR

• Wydawca: Polskie Towarzystwo Matematyczne
• Czasopismo: Fundamenta Informaticae
• Rocznik: 2021
• Tom: Vol. 182, nr 1
• Strony: 69--94
• Opis fizyczny: Rys., wykr.

Twórcy

autor

André Étienne

• Université de Lorraine, CNRS, Inria, LORIA, F-54000 Nancy, France

autor

Lime Didier

• École Centrale de Nantes, LS2N, CNRS, UMR 6004, Nantes, France

autor

Ramparison Mathias

• Université Sorbonne Paris Nord, Villetaneuse, France

autor

Stoelinga Mariëlle

• Formal Methods and Tools, University of Twente, The Netherlands

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023). (PL)