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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/8383
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dc.contributor.authorKumar, Rajesh-
dc.date.accessioned2023-01-09T06:47:34Z-
dc.date.available2023-01-09T06:47:34Z-
dc.date.issued2022-07-
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S1874548222000129-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8383-
dc.description.abstractModern-day industries are complex socio-technical entities. Understanding the risks associated with the operation of such systems requires proper consideration of budget constraints, security expertise and evaluating the effects of legacy services. A relatively newer and unorthodox form of cyber-attacks against such systems are Advanced Persistent Threats (APTs). APTs are resourceful and strategic, aiming at maximum damage by stalling critical services and stealing sensitive information. In this article, we demonstrate how attack trees can be used as a common language to model APT attacks in a practitioner-friendly manner. We do so by modelling three prominent APT attacks, namely Stuxnet, Blackenergy and Triton. Each attack is described in a systematic and structured way following the attack tree modelling language. We show that, because attack trees are compositional models, one can reuse them to model other complex attack scenarios. We illustrate this compositional feature by modelling attacks on an industrial oil-pipeline.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.subjectComputer Scienceen_US
dc.subjectThreat modellingen_US
dc.subjectStuxneten_US
dc.subjectTritonen_US
dc.subjectCyber security risk managementen_US
dc.subjectAdvanced Persistent threatsen_US
dc.titleAPT attacks on industrial control systems: A tale of three incidentsen_US
dc.typeArticleen_US
Appears in Collections:Department of Computer Science and Information Systems

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