An Ontology-based Security Framework for Decision-making in Industrial Systems

Mozzaquatro, Bruno Augusti; Melo, Raquel; Agostinho, Carlos; Jardim‐Gonçalves, Ricardo

doi:10.5220/0005853107790788

Cited by 14 publications

(11 citation statements)

References 15 publications

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“…In [34] the authors provide the security framework for decision support to increase the security of industrial systems. The authors argue that the developed model should be adaptive as soon as the Internet of Things (IoT) is characterized by high variability.…”

Section: Related Workmentioning

confidence: 99%

“…Currently only one approach from the reviewed considers security events. But in scope of that approach the events are added manually during integration of the semantic model with MDD [34]. We believe that introduction of security events and incidents in the ontology itself will allow us to increase its adaptability and automate its modification on fly.…”

Section: Related Workmentioning

confidence: 99%

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A Semantic Model for Security Evaluation of Information Systems

Doynikova

Fedorchenko

Kotenko

2020

JCSANDM

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Modern information systems are characterized by huge security related data streams. For cyber security management in such systems, novel models and techniques for efficient processing of these data streams are required. The paper considers development and application of a semantic model for security evaluation. The proposed model is represented as the ontology of metrics that is based on the relations between sources of security related data, primary features of initial security data and goals of security evaluation. The set of hierarchically interconnected security metrics is mapped to the data features and security evaluation goals. The relations between these metrics within the proposed ontology provide the basis for security evaluation technique. The paper introduces the proposed ontology and its foundations, and briefly describes the developed technique. The analysis of data in the open sources is conducted, and the case study is provided to show applicability of the approach.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

A Semantic Model for Security Evaluation of Information Systems

Doynikova

Fedorchenko

Kotenko

2020

JCSANDM

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“…Ontologies for Industry 4.0 5 (Bunte et al, 2016), product control (Bunte et al, 2016), safety control (Akbari et al, 2010), and security inspection (Mozzaquatro et al, 2016).…”

Section: As Well As System Diagnosismentioning

confidence: 99%

“…On the other hand, production services (Wally et al, 2017) involve abstractions of manufacturing processes (Brodsky et al, 2016;Tang et al, 2018), such as production management (Yusupova et al), product compliance (Disi & Zualkernan, 2009), resource reconfiguration (Wan et al, 2018b), decision support (Arena et al, 2017), and intelligence-based automatization of chain processes (Muller et al, 2018), such as assembly (Merdan et al, 2008;Cecil et al, 2018) and/or diassembly (Koppensteiner et al, 2011), packaging (Wan et al, 2019), shipping (Phutthisathian et al, 2013) as well as system diagnosis Ontologies for Industry 4.0 5 (Bunte et al, 2016), product control (Bunte et al, 2016), safety control (Akbari et al, 2010), and security inspection (Mozzaquatro et al, 2016).…”

Section: Industry 40 Ontological Frameworkmentioning

confidence: 99%

“…Other ontologies have been used for one specific manufacturing process such as packaging (Liu et al, 2005b), process engineering (Wiesner et al, 2010), process compliance (Disi & Zualkernan, 2009), risk management (Atkinson et al, 2006), safety management (Hooi et al, 2012), customer feedback analysis (Kim and Lee, 2013;Daly et al, 2015), organizational management (Grangel-Gonzalez et al, 2016;Izhar and Apduhan, 2017), project management (Cheah et al, 2011), product development (Zhang et al, 2017), maintenance (Haupert et al, 2014), resource reconfiguration (Wan et al, 2018b), and production scheduling (Kourtis et al, 2019). Ontologies have also been focused on one service, for example, ticketing (Vukmirovic et al, 2006), or on one manufacturing concept, for example, information flow (Bildstein and Feng, 2018), information security (Mozzaquatro et al, 2016), and data integration (Yusupova et al).…”

Section: Industry 40 Ontological Frameworkmentioning

confidence: 99%

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Ontologies for Industry 4.0

Ragavan

Khamis

Fiorini³

et al. 2019

The Knowledge Engineering Review

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The current fourth industrial revolution, or 'Industry 4.0' (I4.0), is driven by digital data, connectivity, and cyber systems, and it has the potential to create impressive/new business opportunities. With the arrival of I4.0, the scenario of various intelligent systems interacting reliably and securely with each other becomes a reality which technical systems need to address. One major aspect of I4.0 is to adopt a coherent approach for the semantic communication in between multiple intelligent systems, which include human and artificial (software or hardware) agents. For this purpose, ontologies can provide the solution by formalizing the smart manufacturing knowledge in an interoperable way. Hence, this paper presents the few existing ontologies for I4.0, along with the current state of the standardization effort in the factory 4.0 domain and examples of real-world scenarios for I4.0.

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Security Ontologies: An Investigation of Pitfall Rate

Patel¹,

Debnath²

2022

Data Science With Semantic Technologies

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An Ontology-based Security Framework for Decision-making in Industrial Systems

Cited by 14 publications

References 15 publications

A Semantic Model for Security Evaluation of Information Systems

A Semantic Model for Security Evaluation of Information Systems

Ontologies for Industry 4.0

Security Ontologies: An Investigation of Pitfall Rate

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