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Nowadays, the complexity of cyberattacks has been evolving more and more. Thus, older security systems are struggling to keep up. In this context, fuzzy logic provides an effective way to handle uncertain and ambiguous data, making anomaly detection more accurate and robust. In this research, a model of an adaptive cybersecurity system based on fuzzy sets is proposed which dynamically assesses risks and classifies potential attacks.

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Generalized Net Model of Adapting Systems for Cybersecurity with Intuitionistic Fuzzy Estimations

  • 会议论文

  • 发表日期：

    2025年

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  • Boris Bozveliev,
  • Stanislav Popov

摘要

Nowadays, the complexity of cyberattacks has been evolving more and more. Thus, older security systems are struggling to keep up. In this context, fuzzy logic provides an effective way to handle uncertain and ambiguous data, making anomaly detection more accurate and robust. In this research, a model of an adaptive cybersecurity system based on fuzzy sets is proposed which dynamically assesses risks and classifies potential attacks.