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<p>Jamming attacks are a major problem in Internet of Things (IoT) networks because they disturb wireless communication, slow down the system and affect the reliability. To stop these attacks, we need smart systems that can work well even if data is confusing or missing. “Fuzzy logic-based intrusion detection systems (FLIDS)” are useful in this area because they handle vague information well. However, it is a complex task to choose the best FLIDS, involving many criteria such as detection accuracy, response time, energy use, cost and scalability. This paper introduces a new way to pick the best system using “Hamacher aggregation operators within the <i>p,q,r</i>-cubic Quasi-rung neutrosophic fuzzy set (<i>p,q,r</i>-CQNFS)” framework to solve this decision-making problem. The proposed method is better at representing truth, falsity and indeterminacy more clearly and deals better with uncertainty. A case study on IoT jamming detection demonstrates the application of the model to select the most suitable FLIDS configuration. It also has an evaluation of sensitivity to study the effect of parameter changes, presents the key results and compares the findings with existing methods. The results show that our approach is a reliable way to improve IoT security.</p>

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A Hamacher aggregation-based MCDM approach for optimal selection of FLIDS in IoT jamming detection under cubic quasirung neutrosophic fuzzy structure

  • 期刊论文

  • 发表日期：

    2026年6月29日

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  • Bhavna Mahant,
  • Rakesh Kumar Bajaj,
  • Vikas Baghel

摘要

Jamming attacks are a major problem in Internet of Things (IoT) networks because they disturb wireless communication, slow down the system and affect the reliability. To stop these attacks, we need smart systems that can work well even if data is confusing or missing. “Fuzzy logic-based intrusion detection systems (FLIDS)” are useful in this area because they handle vague information well. However, it is a complex task to choose the best FLIDS, involving many criteria such as detection accuracy, response time, energy use, cost and scalability. This paper introduces a new way to pick the best system using “Hamacher aggregation operators within the p,q,r-cubic Quasi-rung neutrosophic fuzzy set (p,q,r-CQNFS)” framework to solve this decision-making problem. The proposed method is better at representing truth, falsity and indeterminacy more clearly and deals better with uncertainty. A case study on IoT jamming detection demonstrates the application of the model to select the most suitable FLIDS configuration. It also has an evaluation of sensitivity to study the effect of parameter changes, presents the key results and compares the findings with existing methods. The results show that our approach is a reliable way to improve IoT security.