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MATHEMATICAL MODELING OF THE CLONAL SELECTION ALGORITHM IN ARTIFICIAL IMMUNE SYSTEMS FOR THE DETECTION OF DENIAL-OF-SERVICE ATTACKS

Sokolov Alexander Sergeevich  (RTU MIREA )

Artemova Svetlana Valerievna  (Dr. of Engineering, associate professor RTU MIREA )

Potapova Daria Aleksandrovna  (teacher, senior research fellow RTU MIREA )

Brysin Andrey Nikolaevich  (PhD, associate professor MERI RAS, RTU MIREA )

In the article, a mathematical model of the clonal selection algorithm, adapted for detecting denial-of-service (DDoS) attacks within the framework of artificial immune systems, is presented. The process of formalizing the feature spaces of network traffic and the principles of interaction between detectors (antibodies) and network events (antigens) is described. Special attention is given to the mechanisms of cloning, mutation, and selection of detectors, as well as their adaptation to the dynamic conditions of the network environment. The model takes into account the temporal characteristics of network traffic and implements adaptive updating of detectors, ensuring resilience against new and multi-phase attacks. An experimental analysis of the model's effectiveness was conducted using classification quality metrics. The obtained results confirm the applicability of the proposed approach for real-time detection of DDoS attacks.

Keywords:artificial immunity, clonal selection, DDoS attacks, mathematical modeling, anomaly detection, network traffic, information security.
 

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Citation link:
Sokolov A. S., Artemova S. V., Potapova D. A., Brysin A. N. MATHEMATICAL MODELING OF THE CLONAL SELECTION ALGORITHM IN ARTIFICIAL IMMUNE SYSTEMS FOR THE DETECTION OF DENIAL-OF-SERVICE ATTACKS // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2025. -№06/2. -С. 187-192 DOI 10.37882/2223-2966.2025.06-2.36
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