Cyber Danger as One of the Strategic Threats to Russia's Energy Security

Massel, Liudmila; Voropay, N.I.; Senderov, Sergey; Massel, Aleksei

doi:10.21681/2311-3456-2016-4-2-10

Cited by 15 publications

(8 citation statements)

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“…The ES threats list was supplemented with the cybersecurity threats [10], whose implementation could provoke serious emergency situations in the energy sector fraught with a drastic reduction of energy resources to be provided to consumers [11].…”

Section: Modeling Cyber Threats In the Energy Sectormentioning

confidence: 99%

Semantic modeling of cyber threats in the energy sector using Dynamic Cognitive Maps and Bayesian Belief Network

Gaskova¹,

Massel²

2019

Proceedings of the 7th Scientific Conference on Information Technologies for Intelligent Decision Making Support (ITIDS 2019)

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The article discusses the use of semantic modeling in the analysis of threats to energy security (ES). Semantic modeling is proposed to be applied at a qualitative level, followed by quantitative assessment of the ES level in studies of energy security. Exercise of traditional software systems provides a quantitative assessment, which is characterized by the duration of information preparation, and the formation and adjustment of large enough models for computational experiments. At the first level, a decision maker selects options for which a detailed rationale is required based on the results of semantic modeling. These options are calculated at the second level. The article presents basic notions of Dynamic Cognitive Maps (DCM) and Bayesian Belief Network (BBN). The paper presents the information model that is suggested to use in analyzing cyber threats in the energy sector. Exemplification of the impact of cyber threats on an energy facility carried out under Dynamic Cognitive Maps and Bayesian Belief Network is given in this article. The advantages of each tool and their role in analyzing cyber threats in the energy sector are presented.

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Section: Modeling Cyber Threats In the Energy Sectormentioning

confidence: 99%

Semantic modeling of cyber threats in the energy sector using Dynamic Cognitive Maps and Bayesian Belief Network

Gaskova¹,

Massel²

2019

Proceedings of the 7th Scientific Conference on Information Technologies for Intelligent Decision Making Support (ITIDS 2019)

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“…Against the background of rapidly changing external conditions, cyber threats pose an increasing threat to energy objects [5]. It is of great importance to ensure the cybersecurity of automatic control systems, such as relay protection devices, devices of regime and emergency control, automated control systems [6].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the emergency control and relay protection structures approached from the point of view of EPS reliability and survivability by taking into account cybersecurity threats

2019

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Cyber threats pose an increasing threat to energy objects. It is essential to ensure the cybersecurity of automatic control systems, such as relay protection devices (RP), devices of regime control (RC) and emergency control (EC), automated control systems. At the same time, the issues of cybersecurity include not only the problem of hacker attacks, but also the whole complex of problems relating to adequate functioning of cybernetic systems in the power industry. The authors propose a methodical approach to the analysis of the structure of automatic means of regime and emergency control in terms of their impact on the reliability and survivability of power systems (EPS), taking into account the known threats to cybersecurity.

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“…Use of new technologies creates new Cyber Security risks. The threats list to energy security (ES) has been expanded by cyber threats within the context of technological innovations [5].…”

Section: Introductionmentioning

confidence: 99%

Technology of the Intelligent System Application for Cyber Threat Analysis at Energy Facilities

Gaskova¹,

Massel²

2019

Proceedings of the 21st International Workshop on Computer Science and Information Technologies (CSIT 2019)

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The article discusses the methods of system analysis for research of cyber threats to energy facilities. This study proposes application of semantic methods to analyse the impact of cyber threats to energy facilities from the point of view of energy security. Such methods are used under conditions of lack or incompleteness of data on vulnerabilities in software and hardware equipment and on Cyber Security incidents in the energy sector. These methods are also employed in modelling the system behaviour that cannot be accurately forecasted or described formally. The article represents the technology of this Intelligent System application, comprising steps of cyber threats identification, scenarios modelling of extreme situations caused by the implementation of cyber threats, and risk assessment. The technology was developed to evaluate the number of critically vulnerable assets, explain the composition and the likelihood of implementing cyber threats that could cause extreme situations in the energy sector, and to assess risk from their implementation. The deployment of the proposed technology could simplify the process of analysing Cyber Security threats at energy facilities.

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Cyber Danger as One of the Strategic Threats to Russia's Energy Security

Cited by 15 publications

References 0 publications

Semantic modeling of cyber threats in the energy sector using Dynamic Cognitive Maps and Bayesian Belief Network

Semantic modeling of cyber threats in the energy sector using Dynamic Cognitive Maps and Bayesian Belief Network

Analysis of the emergency control and relay protection structures approached from the point of view of EPS reliability and survivability by taking into account cybersecurity threats

Technology of the Intelligent System Application for Cyber Threat Analysis at Energy Facilities

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