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<p>Mobile Ad Hoc Networks (MANETs) are highly dynamic and resource-constrained systems in which the resourceful maintenance of secure, energy-efficient, and trustworthy communication is challenging owing to frequent changes in topologies and highly malicious intrusions. To resolve these issues, this work proposes research will provide a Hybrid Intelligence-Powered Secure Clustering and Trust-Optimized Routing (HISCTR) framework that combines adaptive clustering, intelligent trust assessment, and hybrid deep-learning-based intrusion detection into a single architecture. The Geographical Adaptive Fidelity Clustering (GAFC) scheme provides stable clustering, whereas the Addax Optimization Algorithm (AOA) identifies energy-balanced Cluster Heads and Sub-Cluster Heads according to residual energy, centrality, and mobility. Fuzzy Trust Vector Computation (FTVC) and Halfway Escape Optimization (HEO) are further used to provide routing reliability, as they collaboratively determine low-delay and highly trusted communication paths. Transformer-based temporal learning and CNN-based spatial analysis allow for a dual-path anomaly detection module to ensure the complete detection of multiple attacks. The proposed model showed the best performance at a mean power use of 0.8&#xa0;mJ, throughput of 0.92 Mbps, packet delivery ratio, 5300-round network life, and efficiency rate of 99.5%, as proven by extensive simulations. These findings verify that HISCTR can provide a security-conscious, scalable, and robust communication system for next-generation MANETs.</p>

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Hybrid intelligence-powered secure clustering with trust-optimized routing for next-generation MANET communication

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月10日

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  • T. Anuprathibha,
  • R. Maheswari,
  • A. Suresh Babu,
  • S. Murugesan

摘要

Mobile Ad Hoc Networks (MANETs) are highly dynamic and resource-constrained systems in which the resourceful maintenance of secure, energy-efficient, and trustworthy communication is challenging owing to frequent changes in topologies and highly malicious intrusions. To resolve these issues, this work proposes research will provide a Hybrid Intelligence-Powered Secure Clustering and Trust-Optimized Routing (HISCTR) framework that combines adaptive clustering, intelligent trust assessment, and hybrid deep-learning-based intrusion detection into a single architecture. The Geographical Adaptive Fidelity Clustering (GAFC) scheme provides stable clustering, whereas the Addax Optimization Algorithm (AOA) identifies energy-balanced Cluster Heads and Sub-Cluster Heads according to residual energy, centrality, and mobility. Fuzzy Trust Vector Computation (FTVC) and Halfway Escape Optimization (HEO) are further used to provide routing reliability, as they collaboratively determine low-delay and highly trusted communication paths. Transformer-based temporal learning and CNN-based spatial analysis allow for a dual-path anomaly detection module to ensure the complete detection of multiple attacks. The proposed model showed the best performance at a mean power use of 0.8 mJ, throughput of 0.92 Mbps, packet delivery ratio, 5300-round network life, and efficiency rate of 99.5%, as proven by extensive simulations. These findings verify that HISCTR can provide a security-conscious, scalable, and robust communication system for next-generation MANETs.