{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T00:07:06Z","timestamp":1768349226800,"version":"3.49.0"},"reference-count":39,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2024,11,4]],"date-time":"2024-11-04T00:00:00Z","timestamp":1730678400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["BDCC"],"abstract":"<jats:p>In recent years, cybersecurity management has increasingly required advanced methodologies capable of handling complex, evolving threat landscapes. Scenario network-based approaches have emerged as effective strategies for managing uncertainty and adaptability in cybersecurity projects. This article introduces a scenario network-based approach for managing cybersecurity projects, utilizing fuzzy linguistic models and a Takagi\u2013Sugeno\u2013Kanga fuzzy neural network. Drawing upon L. Zadeh\u2019s theory of linguistic variables, the methodology integrates expert analysis, linguistic variables, and a continuous genetic algorithm to predict membership function parameters. Fuzzy production rules are employed for decision-making, while the Mamdani fuzzy inference algorithm enhances interpretability. This approach enables multi-scenario planning and adaptability across multi-stage cybersecurity projects. Preliminary results from a research prototype of an intelligent expert system\u2014designed to analyze project stages and adaptively construct project trajectories\u2014suggest the proposed approach is effective. In computational experiments, the use of fuzzy procedures resulted in an over 25% reduction in errors compared to traditional methods, particularly in adjusting project scenarios from pessimistic to baseline projections. While promising, this approach requires further testing across diverse cybersecurity contexts. Future studies will aim to refine scenario adaptation and optimize system response in high-risk project environments.<\/jats:p>","DOI":"10.3390\/bdcc8110150","type":"journal-article","created":{"date-parts":[[2024,11,4]],"date-time":"2024-11-04T09:52:54Z","timestamp":1730713974000},"page":"150","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Adaptive Management of Multi-Scenario Projects in Cybersecurity: Models and Algorithms for Decision-Making"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3959-2969","authenticated-orcid":false,"given":"Vadim","family":"Tynchenko","sequence":"first","affiliation":[{"name":"Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia"},{"name":"Department of Information and Control Systems, Reshetnev Siberian State University of Science and Technology, 660037 Krasnoyarsk, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5816-7792","authenticated-orcid":false,"given":"Alexander","family":"Lomazov","sequence":"additional","affiliation":[{"name":"Department of Data Analysis and Machine Learning, Financial University, 125167 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vadim","family":"Lomazov","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Physics, Chemistry and Information Technologies, Belgorod State Agricultural University Named After V. Gorin, 308503 Belgorod, Russia"},{"name":"Department of Applied Informatics and Information Technology, Belgorod State University, 308015 Belgorod, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dmitry","family":"Evsyukov","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vladimir","family":"Nelyub","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia"},{"name":"Scientific Department, Far Eastern Federal University, 690922 Vladivostok, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aleksei","family":"Borodulin","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrei","family":"Gantimurov","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-8986-402X","authenticated-orcid":false,"given":"Ivan","family":"Malashin","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Peltier, T.R. (2005). Information Security Risk Analysis, CRC Press Taylor & Francis Group. [3rd ed.].","DOI":"10.1201\/9781420031195"},{"key":"ref_2","unstructured":"Seacord, R.C., and Householder, A.D. (2024, September 26). A Structured Approach to Classifying Security Vulnerabilities. Available online: https:\/\/citeseerx.ist.psu.edu\/document?repid=rep1&type=pdf&doi=6baac91ec76b059d7d7807c6706d8279d5afac08."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"602","DOI":"10.3390\/encyclopedia1030050","article-title":"Information Security Risk Assessment","volume":"1","author":"Kuzminykh","year":"2021","journal-title":"Encyclopedia"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"655","DOI":"10.1016\/j.promfg.2020.02.243","article-title":"Risk Based Approach in Scope of Cybersecurity Threats and Requirements","volume":"44","author":"Hoffmann","year":"2020","journal-title":"Procedia Manuf."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1080\/19361610.2021.1918995","article-title":"A Conceptual Model for Cybersecurity Governance","volume":"16","author":"Yusif","year":"2021","journal-title":"J. Appl. Secur. Res."},{"key":"ref_6","first-page":"49","article-title":"Investing in Cybersecurity: Insights from the Gordon-Loeb Model","volume":"7","author":"Gordon","year":"2021","journal-title":"J. Inf. Secur."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"659","DOI":"10.1016\/j.bushor.2021.02.022","article-title":"Cybersecurity: Risk Management Framework and Investment Cost Analysis","volume":"64","author":"Lee","year":"2021","journal-title":"Bus. Horizons"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"10","DOI":"10.5585\/gep.v13i3.23083","article-title":"A Framework for the Planning and Management of Cybersecurity Projects in Small and Medium-Sized Enterprises","volume":"13","author":"Franco","year":"2022","journal-title":"Rev. Gest\u00e3O Proj. (GeP)"},{"key":"ref_9","first-page":"45","article-title":"A Precedent Approach to Incident Management in Automated Process Control Systems","volume":"2020","author":"Dobrynin","year":"2020","journal-title":"Softw. Syst. Comput. Methods"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Kulakov, S., Trofimov, V., Dobrynin, A., and Taraborina, E. (2018). Precedent Approach to the Formation of Programs for Cyclic Objects Control. IOP Conf. Ser. Mater. Sci. Eng., 354.","DOI":"10.1088\/1757-899X\/354\/1\/012002"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Sarker, I.H., Janicke, H., Ferrag, M.A., and Abuadbba, A. (2024). Multi-aspect rule-based AI: Methods, taxonomy, challenges and directions toward automation, intelligence and transparent cybersecurity modeling for critical infrastructures. Internet Things, 25.","DOI":"10.1016\/j.iot.2024.101110"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1748","DOI":"10.1109\/COMST.2023.3273282","article-title":"Cyber threat intelligence mining for proactive cybersecurity defense: A survey and new perspectives","volume":"25","author":"Sun","year":"2023","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_13","first-page":"1","article-title":"Natural Language Processing for Detecting Anomalies and Intrusions in Unstructured Cybersecurity Data","volume":"7","author":"Sharma","year":"2023","journal-title":"Int. J. Inf. Cybersecur."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"935","DOI":"10.1016\/j.icte.2024.05.007","article-title":"Explainable AI for cybersecurity automation, intelligence and trustworthiness in digital twin: Methods, taxonomy, challenges and prospects","volume":"10","author":"Sarker","year":"2024","journal-title":"ICT Express"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Sarker, I.H. (2023). Multi-aspects AI-based modeling and adversarial learning for cybersecurity intelligence and robustness: A comprehensive overview. Secur. Priv., 6.","DOI":"10.1002\/spy2.295"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Malatji, M., and Tolah, A. (2024). Artificial intelligence (AI) cybersecurity dimensions: A comprehensive framework for understanding adversarial and offensive AI. AI and Ethics, Spinger.","DOI":"10.1007\/s43681-024-00427-4"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"374","DOI":"10.1016\/j.aej.2024.07.044","article-title":"A data-driven multi-perspective approach to cybersecurity knowledge discovery through topic modelling","volume":"107","author":"Alqurashi","year":"2024","journal-title":"Alex. Eng. J."},{"key":"ref_18","unstructured":"Kozhakhmet, K., Bortsova, G., Inoue, A., and Atymtayeva, L. (2012, January 21\u201322). Expert System for Security Audit Using Fuzzy Logic. Proceedings of the Midwest Artificial Intelligence and Cognitive Science Conference, Cincinnati, OH, USA."},{"key":"ref_19","first-page":"119","article-title":"The Concept of a Linguistic Variable and its Application to Approximate Reasoning","volume":"1","author":"Zadeh","year":"1975","journal-title":"Inf. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2923","DOI":"10.1016\/j.ins.2011.02.022","article-title":"A Note on Z-Numbers","volume":"181","author":"Zadeh","year":"2011","journal-title":"Inf. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1007\/s12652-012-0137-8","article-title":"An Inference Engine Toolkit for Computing with Words","volume":"4","author":"Khorasani","year":"2013","journal-title":"J. Ambient. Intell. Humaniz. Comput."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Vignieri, V. (2018). Performance Management in the Public Sector. Global Encyclopedia of Public Administration, Public Policy, and Governance, Springer International Publishing.","DOI":"10.1007\/978-3-319-31816-5_3480-1"},{"key":"ref_23","unstructured":"(2024, October 28). The Standard of the Bank of Russia STO BR IBBS-1.2-2014: Ensuring Information Security of Organizations of the Banking System of the Russian Federation. Available online: https:\/\/cbr.ru\/statichtml\/file\/59420\/st-12-14.pdf."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Patwary, A.A.N., Naha, R.K., Garg, S., Battula, S.K., Patwary, M.A.K., Aghasian, E., Amin, M.B., Mahanti, A., and Gong, M. (2021). Towards secure fog computing: A survey on trust management, privacy, authentication, threats and access control. Electronics, 10.","DOI":"10.3390\/electronics10101171"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Aslan, \u00d6., Aktu\u011f, S.S., Ozkan-Okay, M., Yilmaz, A.A., and Akin, E. (2023). A comprehensive review of cyber security vulnerabilities, threats, attacks, and solutions. Electronics, 12.","DOI":"10.3390\/electronics12061333"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Das, M., Tao, X., Liu, Y., and Cheng, J.C. (2022). A blockchain-based integrated document management framework for construction applications. Autom. Constr., 133.","DOI":"10.1016\/j.autcon.2021.104001"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Pizam, A., Ozturk, A.B., Hacikara, A., Zhang, T., Balderas-Cejudo, A., Buhalis, D., Fuchs, G., Hara, T., Meira, J., and Revilla, R.G.M. (2024). The role of perceived risk and information security on customers\u2019 acceptance of service robots in the hotel industry. Int. J. Hosp. Manag., 117.","DOI":"10.1016\/j.ijhm.2023.103641"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Santos-Olmo, A., S\u00e1nchez, L.E., Rosado, D.G., Serrano, M.A., Blanco, C., Mouratidis, H., and Fern\u00e1ndez-Medina, E. (2024). Towards an integrated risk analysis security framework according to a systematic analysis of existing proposals. Front. Comput. Sci., 18.","DOI":"10.1007\/s11704-023-1582-6"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"48608","DOI":"10.1109\/ACCESS.2024.3383917","article-title":"A Multi-Criteria Decision-Making for Legacy System Modernization With FUCOM-WSM Approach","volume":"12","author":"Jomhari","year":"2024","journal-title":"IEEE Access"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Liu, Y., Hu, Y., Shen, K., Qiu, J., and Neusypin, K.A. (2024). Integral Reinforcement Learning-Based Angular Acceleration Autopilot for High Dynamic Flight Vehicles. Appl. Soft Comput., 158.","DOI":"10.1016\/j.asoc.2024.111582"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Adam, F., and Humphreys, P. (2008). Encyclopedia of Decision Making and Decision Support Technologies, Hershey.","DOI":"10.4018\/978-1-59904-843-7"},{"key":"ref_32","first-page":"251","article-title":"Relative Measurement and Its Generalization in Decision Making: Why Pairwise Comparisons Are Central in Mathematics for the Measurement of Intangible Factors - The Analytic Hierarchy\/Network Process","volume":"102","author":"Saaty","year":"2008","journal-title":"Rev. R. Span. Acad. Sci. Ser. A Math."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Burkov, V.N., Burkova, I.V., Gorgidze, I.A., Burkov, V.N., Burkova, I.V., Gorgidze, I.A., Gochitashvili, L.I., Kajaia, T.N., Lominadze, T.N., and Khartishvili, M.P. (2012). The Method of Network Programming for the Project Management. Information and Computer Technologies\u2014Theory and Practice: Proceedings of the International Scientific Conference ICTMC-2010 Devoted to the 80th Anniversary of I.V. Prangishvili, Nova Science Publishers Inc.","DOI":"10.1049\/ic.2010.0275"},{"key":"ref_34","first-page":"26","article-title":"Fuzzy Threat Analysis and the Choice of Options for the Information Security System of an Innovative Project","volume":"10","author":"Lomazov","year":"2017","journal-title":"Mod. High-Tech Technol."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Ptuskin, A., Levner, E., and Kats, V. (2024). Cyclic Multi-Hoist Scheduling with Fuzzy Processing Times in Flexible Manufacturing Lines. Appl. Soft Comput., 165.","DOI":"10.1016\/j.asoc.2024.112014"},{"key":"ref_36","unstructured":"Russell, S.J., and Norvig, P. (2020). Artificial Intelligence: A Modern Approach, Prentice Hall."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1109\/TSMC.1985.6313399","article-title":"Fuzzy Identification of Systems and Its Applications to Modeling and Control","volume":"SMC-15","author":"Takagi","year":"1985","journal-title":"IEEE Trans. Syst. Man, Cybern."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/0165-0114(88)90113-3","article-title":"Structure Identification of Fuzzy Model","volume":"28","author":"Sugeno","year":"1988","journal-title":"Fuzzy Sets Syst."},{"key":"ref_39","first-page":"703","article-title":"Method of Converting Z-Number to Classical Fuzzy Number","volume":"9","author":"Kang","year":"2012","journal-title":"J. Inf. Comput. Sci."}],"container-title":["Big Data and Cognitive Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2504-2289\/8\/11\/150\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:28:22Z","timestamp":1760113702000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2504-2289\/8\/11\/150"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,4]]},"references-count":39,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2024,11]]}},"alternative-id":["bdcc8110150"],"URL":"https:\/\/doi.org\/10.3390\/bdcc8110150","relation":{},"ISSN":["2504-2289"],"issn-type":[{"value":"2504-2289","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,4]]}}}