IDEAS home Printed from https://ideas.repec.org/a/gam/jdataj/v8y2023i10p156-d1263099.html
   My bibliography  Save this article

Cybersecurity Risk Assessments within Critical Infrastructure Social Networks

Author

Listed:
  • Alimbubi Aktayeva

    (Department of Information Systems and Informatics, Abay Myrzakhmetov Kokshetau University, Kokshetau 000002, Kazakhstan)

  • Yerkhan Makatov

    (Department of Information Security, L. N. Gumilyov Eurasian National University, Astana 010000, Kazakhstan)

  • Akku Kubigenova Tulegenovna

    (Department of Information Systems, S. Seifullin Kazakh Agrotechnical University, Astana 010000, Kazakhstan)

  • Aibek Dautov

    (Department of Information Systems and Informatics, Abay Myrzakhmetov Kokshetau University, Kokshetau 000002, Kazakhstan)

  • Rozamgul Niyazova

    (Department of Artificial Intelligence Technologies, L. N. Gumilyov Eurasian National University, Astana 010000, Kazakhstan)

  • Maxud Zhamankarin

    (Department of Information Systems and Informatics, Abay Myrzakhmetov Kokshetau University, Kokshetau 000002, Kazakhstan)

  • Sergey Khan

    (Department of Information and Communication Technologies, Sh. Ualikhanov Kokshetau University, Kokshetau 000002, Kazakhstan)

Abstract

Cybersecurity social networking is a new scientific and engineering discipline that was interdisciplinary in its early days, but is now transdisciplinary. The issues of reviewing and analyzing of principal tasks related to information collection, monitoring of social networks, assessment methods, and preventing and combating cybersecurity threats are, therefore, essential and pending. There is a need to design certain methods, models, and program complexes aimed at estimating risks related to the cyberspace of social networks and the support of their activities. This study considers a risk to be the combination of consequences of a given event (or incident) with a probable occurrence (likelihood of occurrence) involved, while risk assessment is a general issue of identification, estimation, and evaluation of risk. The findings of the study made it possible to elucidate that the technique of cognitive modeling for risk assessment is part of a comprehensive cybersecurity approach included in the requirements of basic IT standards, including IT security risk management. The study presents a comprehensive approach in the field of cybersecurity in social networks that allows for consideration of all the elements that constitute cybersecurity as a complex, interconnected system. The ultimate goal of this approach to cybersecurity is the organization of an uninterrupted scheme of protection against any impacts related to physical, hardware, software, network, and human objects or resources of the critical infrastructure of social networks, as well as the integration of various levels and means of protection.

Suggested Citation

  • Alimbubi Aktayeva & Yerkhan Makatov & Akku Kubigenova Tulegenovna & Aibek Dautov & Rozamgul Niyazova & Maxud Zhamankarin & Sergey Khan, 2023. "Cybersecurity Risk Assessments within Critical Infrastructure Social Networks," Data, MDPI, vol. 8(10), pages 1-18, October.
    • Handle: RePEc:gam:jdataj:v:8:y:2023:i:10:p:156-:d:1263099
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2306-5729/8/10/156/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2306-5729/8/10/156/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zio, Enrico, 2016. "Challenges in the vulnerability and risk analysis of critical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 137-150.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tang, Daogui & Fang, Yi-Ping & Zio, Enrico, 2023. "Vulnerability analysis of demand-response with renewable energy integration in smart grids to cyber attacks and online detection methods," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    2. Federico Antonello & Piero Baraldi & Enrico Zio & Luigi Serio, 2022. "A Novel Metric to Evaluate the Association Rules for Identification of Functional Dependencies in Complex Technical Infrastructures," Environment Systems and Decisions, Springer, vol. 42(3), pages 436-449, September.
    3. Zhaoming Yang & Qi Xiang & Yuxuan He & Shiliang Peng & Michael Havbro Faber & Enrico Zio & Lili Zuo & Huai Su & Jinjun Zhang, 2023. "Resilience of Natural Gas Pipeline System: A Review and Outlook," Energies, MDPI, vol. 16(17), pages 1-19, August.
    4. Luciano Cavalcante Siebert & Alexandre Rasi Aoki & Germano Lambert-Torres & Nelson Lambert-de-Andrade & Nikolaos G. Paterakis, 2020. "An Agent-Based Approach for the Planning of Distribution Grids as a Socio-Technical System," Energies, MDPI, vol. 13(18), pages 1-13, September.
    5. Zio, E., 2018. "The future of risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 176-190.
    6. Dubaniowski, Mateusz Iwo & Heinimann, Hans Rudolf, 2021. "Framework for modeling interdependencies between households, businesses, and infrastructure system, and their response to disruptions—application," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    7. Mohamed Gaha & Bilal Chabane & Dragan Komljenovic & Alain Côté & Claude Hébert & Olivier Blancke & Atieh Delavari & Georges Abdul-Nour, 2021. "Global Methodology for Electrical Utilities Maintenance Assessment Based on Risk-Informed Decision Making," Sustainability, MDPI, vol. 13(16), pages 1-23, August.
    8. Senderov, Sergey M. & Smirnova, Elena M. & Vorobev, Sergey V., 2020. "Analysis of vulnerability of fuel supply systems in gas-consuming regions due to failure of critical gas industry facilities," Energy, Elsevier, vol. 212(C).
    9. Kefan Xie & Zimei Liu, 2019. "Factors Influencing Escalator-Related Incidents in China: A Systematic Analysis Using ISM-DEMATEL Method," IJERPH, MDPI, vol. 16(14), pages 1-15, July.
    10. Yi‐Ping Fang & Giovanni Sansavini & Enrico Zio, 2019. "An Optimization‐Based Framework for the Identification of Vulnerabilities in Electric Power Grids Exposed to Natural Hazards," Risk Analysis, John Wiley & Sons, vol. 39(9), pages 1949-1969, September.
    11. Mühlhofer, Evelyn & Koks, Elco E. & Kropf, Chahan M. & Sansavini, Giovanni & Bresch, David N., 2023. "A generalized natural hazard risk modelling framework for infrastructure failure cascades," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    12. Wang, WuChang & Zhang, Yi & Li, YuXing & Hu, Qihui & Liu, Chengsong & Liu, Cuiwei, 2022. "Vulnerability analysis method based on risk assessment for gas transmission capabilities of natural gas pipeline networks," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    13. Lu, Xuefei & Baraldi, Piero & Zio, Enrico, 2020. "A data-driven framework for identifying important components in complex systems," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    14. Hao, Zhaojun & Di Maio, Francesco & Zio, Enrico, 2023. "A sequential decision problem formulation and deep reinforcement learning solution of the optimization of O&M of cyber-physical energy systems (CPESs) for reliable and safe power production and supply," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    15. Liu, Xing & Ferrario, Elisa & Zio, Enrico, 2019. "Identifying resilient-important elements in interdependent critical infrastructures by sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 423-434.
    16. Tianlei Zang & Zian Wang & Xiaoguang Wei & Yi Zhou & Jiale Wu & Buxiang Zhou, 2023. "Current Status and Perspective of Vulnerability Assessment of Cyber-Physical Power Systems Based on Complex Network Theory," Energies, MDPI, vol. 16(18), pages 1-38, September.
    17. F. Brocal & C. González & D. Komljenovic & P. F. Katina & Miguel A. Sebastián, 2019. "Emerging Risk Management in Industry 4.0: An Approach to Improve Organizational and Human Performance in the Complex Systems," Complexity, Hindawi, vol. 2019, pages 1-13, June.
    18. Rocchetta, Roberto, 2022. "Enhancing the resilience of critical infrastructures: Statistical analysis of power grid spectral clustering and post-contingency vulnerability metrics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    19. Liu, Xing & Fang, Yi-Ping & Zio, Enrico, 2021. "A Hierarchical Resilience Enhancement Framework for Interdependent Critical Infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    20. Federico Antonello & Piero Baraldi & Enrico Zio & Luigi Serio, 2022. "A novelty-based multi-objective evolutionary algorithm for identifying functional dependencies in complex technical infrastructures from alarm data," Environment Systems and Decisions, Springer, vol. 42(2), pages 177-188, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jdataj:v:8:y:2023:i:10:p:156-:d:1263099. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.