Because of modern societies' dependence on industrial control systems, adequate response to system failures is essential. In order to take appropriate measures, it is crucial for operators to be able to distinguish between intentional attacks and accidental technical failures. However, adequate decision support for this matter is lacking. In this paper, we use Bayesian Networks (BNs) to distinguish between intentional attacks and accidental technical failures, based on contributory factors and observations (or test results). To facilitate knowledge elicitation, we use extended fishbone diagrams for discussions with experts, and then translate those into the BN formalism. We demonstrate the methodology using an example in a case study from the water management domain.
Original languageEnglish
Title of host publicationGraphical Models for Security - 5th International Workshop, GraMSec 2018, Revised Selected Papers
Subtitle of host publicationGraphical Models for Security
EditorsDavid Pym, Barbara Fila, George Cybenko
PublisherSpringer
Pages31-50
Number of pages20
ISBN (Electronic)978-3-030-15465-3
ISBN (Print)978-3-030-15464-6
DOIs
Publication statusPublished - Mar 2019
EventThe Fifth International Workshop on Graphical Models for Security - Mathematical Institute, University of Oxford, Oxford, United Kingdom
Duration: 8 Jul 20188 Jul 2018
http://gramsec.uni.lu/

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11086 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Workshop

WorkshopThe Fifth International Workshop on Graphical Models for Security
Abbreviated titleGraMSec
CountryUnited Kingdom
CityOxford
Period8/07/188/07/18
Internet address

    Research areas

  • Bayesian Network, Fishbone Diagram, Intentional Attack, Safety, Security, Technical Failure

ID: 52764441