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<p>Vehicular Ad Hoc Network (VANET) is essential in critical infrastructure surveillance and cyber-physical systems. It is yet very difficult to provide strong cyber security while preserving effective energy use and quality of service (QoS) to transmit the data in VANET. By efficiently encompassing additional nodes, mobile data collectors (MDCs) offer a viable solution to the energy hole challenge. However, designing MDC trajectories and calculating optimal data gathering points (GPs) are NP-hard problems. This research introduces an innovative data collecting technique which utilizes particle swarm-driven snow ablation optimization (PS-SAO) for prioritizing the QoS indicators, raising the level of energy efficacy, as well as strengthening the network’s security and detection the cyber-attacks. QoS problems are taken into account when generating a multi-functional fitness meters for assessing the caliber of the selected general practitioners. The simulation outcomes display that the recommended protocols are effective of CH quantity, entire energy consumed and network’s lifespan. The proposed approach achieved better results including recommended protocols are effective in accuracy (98.48%), precision (98.91%), recall (98.12%) and F1-score (98.21%), and reduced computational time (120.4&#xa0;s). The protocol is perfect for systems requiring robust cyber security in circumstances with restricted resources due to its flexibility in adapting to varying network conditions and its capability to lower security risks.</p>

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A Secure and Energy-Efficient Framework for Data Collection and Threat Detection in VANETs

  • 期刊论文

  • 发表日期：

    2026年2月12日

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  • Prabhat Kumar Sahu,
  • S. Raghunathan,
  • Divya Piakaray,
  • Anand Kumar Gupta,
  • Afroj Alam

摘要

Vehicular Ad Hoc Network (VANET) is essential in critical infrastructure surveillance and cyber-physical systems. It is yet very difficult to provide strong cyber security while preserving effective energy use and quality of service (QoS) to transmit the data in VANET. By efficiently encompassing additional nodes, mobile data collectors (MDCs) offer a viable solution to the energy hole challenge. However, designing MDC trajectories and calculating optimal data gathering points (GPs) are NP-hard problems. This research introduces an innovative data collecting technique which utilizes particle swarm-driven snow ablation optimization (PS-SAO) for prioritizing the QoS indicators, raising the level of energy efficacy, as well as strengthening the network’s security and detection the cyber-attacks. QoS problems are taken into account when generating a multi-functional fitness meters for assessing the caliber of the selected general practitioners. The simulation outcomes display that the recommended protocols are effective of CH quantity, entire energy consumed and network’s lifespan. The proposed approach achieved better results including recommended protocols are effective in accuracy (98.48%), precision (98.91%), recall (98.12%) and F1-score (98.21%), and reduced computational time (120.4 s). The protocol is perfect for systems requiring robust cyber security in circumstances with restricted resources due to its flexibility in adapting to varying network conditions and its capability to lower security risks.