MULTI-CRITERIA OPTIMIZATION METHOD FOR CLOUD COMPUTING SECURITY BASED ON A MODIFIED NSGA-II ALGORITHM
DOI:
https://doi.org/10.28925/2663-4023.2025.30.983Keywords:
cloud computing, resource allocation, cybersecurity, game theory, cooperative games, coalition games, evolutionary optimization, NSGA-II, dynamic risk, multi-criteria optimization.Abstract
This article is devoted to the development and analysis of an extended hybrid model for cloud security that integrates evolutionary optimization, game theory, and cooperative strategies with dynamic risk considerations. The proposed CoopEvo-CloudSec method is based on a modification of the NSGA-II algorithm that takes into account four key criteria: security level, task processing time, resource cost, and coalitional benefit from joint protection. The goal of the study is to create an effective mechanism for distributing computing resources in cloud systems that would optimize performance and security under variable risks. For this purpose, a hybrid approach is used that combines theoretical attacker-defender models with evolutionary algorithms and cooperative strategies based on the Shapley value to assess the contribution of each node to the coalition of defenders. The computational experiment was conducted in the PyCharm environment using synthetic and real datasets. The experimental results demonstrate the superiority of the proposed model over the basic NSGA-II and other options. In particular, the CoopEvo-CloudSec method achieves a better balance between quality metrics, such as normalized hypervolume (1.0145), evenness of solution distribution and diversity (Diversity >1.2), with a moderate execution time (70–80 s). Comparative analysis on radar diagrams, boxplots and parallel coordinates confirms the ability of the model to generate Pareto-optimal solutions adapted to different threat scenarios, including dynamic changes in the risk indicator λ(t). Statistical tests (ANOVA and Tukey) prove the significance of the differences, with a coefficient of variation of 14.07% for stability. The method has practical importance for cloud service providers, as it facilitates the implementation of Zero Trust architectures and hybrid cryptographic schemes (e.g. AES+ECC). Overall, the study offers an innovative tool for risk management in cloud environments that meets modern cybersecurity challenges and contributes to the development of hybrid systems.
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