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MODEL FOR ASSESSMENT OF CYBER RESILIENCE OF INFORMATION SYSTEMS OF CRITICAL INFRASTRUCTURE OBJECTS UNDER THE INFLUENCE OF HYBRID CYBER ATTACKS USING MACHINE LEARNING ALGORITHMS

MODEL FOR ASSESSMENT OF CYBER RESILIENCE OF INFORMATION SYSTEMS OF CRITICAL INFRASTRUCTURE OBJECTS UNDER THE INFLUENCE OF HYBRID CYBER ATTACKS USING MACHINE LEARNING ALGORITHMS

Abstract

The article presents a model for assessing the cyber resilience of information systems of critical infrastructure objects (CIO) under the influence of combined cyber attacks. The model analyzes the impact of ten types of attacks, such as DoS, DDoS, phishing, malware, and others, on HMI and SCADA systems. The interaction between attacks and systems is modeled using the Monte Carlo method; a genetic algorithm is used to create hybrid attacks, and clustering with HDBSCAN allows for determining the resilience of systems to certain types of attacks. Prediction of attack consequences and recovery time is carried out using the Random Forest Regressor algorithm. The research results can be used to improve cyber defense measures of CIOs and enhance their ability to recover after cyber attacks. У статті представлено модель оцінювання кіберстійкості інформаційних систем об'єктів критичної інфраструктури (ОКІ) під впливом комбінованих кібератак. Модель аналізує вплив десяти типів атак, таких як DoS, DDoS, фішинг, шкідливе програмне забезпечення та інші, на системи HMI та SCADA. Взаємодія між атаками та системами моделюється через метод Монте-Карло, генетичний алгоритм використовується для створення гібридних атак, а кластеризація за допомогою HDBSCAN дозволяє визначити стійкість систем до певних типів атак. Прогнозування наслідків атак та часу відновлення здійснюється за допомогою алгоритму Random Forest Regressor. Результати дослідження можуть бути використані для вдосконалення заходів кіберзахисту ОКІ та підвищення їх здатності до відновлення після кібератак.

Keywords

кібератака, assessment, симуляція, гібридні загрози, cyber resilience, hybrid threats, машинне навчання, information systems, ОКІ, genetic algorithm, SCADA, інформаційні системи, кібербезпека, recovery time, HMI, cyber attack, CIO, cyber security, критична інфраструктура, кіберстійкість, modeling, оцінювання, simulation, генетичний алгоритм, machine learning, critical infrastructure, відновлення, моделювання

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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