COMPREHENSIVE MODEL FOR SELECTING ANTIVIRUS SOFTWARE FOR CRITICAL INFRASTRUCTURE FACILITIES

The rapid growth of cyber attacks on critical infrastructure against the backdrop of rapid development of information technology highlights the urgent need for effective protection mechanisms. This study examines the problem of choosing the best antivirus software, which is complicated by the increasing complexity of decision-making and the limitations of current approaches. The article presents a detailed, comprehensive mathematical model designed to automate the process of selecting antivirus software. This model uses multi-criteria analysis and expert assessments to ensure flexibility and objectivity. It evaluates technical characteristics such as detection probability, false positive rate, performance, system load, response time, and database update frequency, as well as operational risks and the Common Vulnerability Scoring System (CVSS). The methodology uses geometric mean aggregation of expert opinions and checks their consistency to reduce subjectivity and increase reliability. Two methods of incorporating the risk factor into the overall assessment were tested, allowing adaptation to different strategic goals. Experimental results confirmed the effectiveness of the model in determining optimal antivirus solutions for mission-critical information systems. The model effectively processes expert data and creates organised information for decision-making. Further research could expand the model's knowledge base, improve decision-making algorithms for new cyber threats, and adapt it for wider application in information security.

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Publication Details

Journal
Cybersecurity Education Science Technique
Published
2025-01-01
DOI
https://doi.org/10.28925/2663-4023.2025.29.929
Primary Topic
Information and Cyber Security
Type
article
Field-Weighted Citation Impact
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article

COMPREHENSIVE MODEL FOR SELECTING ANTIVIRUS SOFTWARE FOR CRITICAL INFRASTRUCTURE FACILITIES

Serhii Buchyk, Maksym Maievskyi
Cybersecurity Education Science Technique
Information and Cyber Security
article

COMPREHENSIVE MODEL FOR SELECTING ANTIVIRUS SOFTWARE FOR CRITICAL INFRASTRUCTURE FACILITIES

Serhii Buchyk, Maksym Maievskyi
article en

Abstract

The rapid growth of cyber attacks on critical infrastructure against the backdrop of rapid development of information technology highlights the urgent need for effective protection mechanisms. This study examines the problem of choosing the best antivirus software, which is complicated by the increasing complexity of decision-making and the limitations of current approaches. The article presents a detailed, comprehensive mathematical model designed to automate the process of selecting antivirus software. This model uses multi-criteria analysis and expert assessments to ensure flexibility and objectivity. It evaluates technical characteristics such as detection probability, false positive rate, performance, system load, response time, and database update frequency, as well as operational risks and the Common Vulnerability Scoring System (CVSS). The methodology uses geometric mean aggregation of expert opinions and checks their consistency to reduce subjectivity and increase reliability. Two methods of incorporating the risk factor into the overall assessment were tested, allowing adaptation to different strategic goals. Experimental results confirmed the effectiveness of the model in determining optimal antivirus solutions for mission-critical information systems. The model effectively processes expert data and creates organised information for decision-making. Further research could expand the model's knowledge base, improve decision-making algorithms for new cyber threats, and adapt it for wider application in information security.

Cybersecurity Education Science TechniqueVol. 1(29)
Taras Shevchenko National University of Kyiv (UA)
Openalex Percentile: Top 60%
Information and Cyber Security
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COMPREHENSIVE MODEL FOR SELECTING ANTIVIRUS SOFTWARE FOR CRITICAL INFRASTRUCTURE FACILITIES — Serhii Buchyk, Maksym Maievskyi · Cybersecurity Education Science Technique (2025) | TGRS Research Map | TGRS