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<p>Wireless Sensor Networks (WSNs) encounter significant issues in managing both security and energy efficiency due to the limitations of current solutions. The high energy consumption associated with secure data transmission often leads to rapid battery depletion in Sensor Nodes (SNs), compromising the network's overall longevity and performance. Furthermore, existing methods often overlook critical factors such as network delay, data integrity, SNs trust, and potential security breaches. To address these issues, this research proposes a novel KAPOA-IAES-based routing approach (KAPOA-IAES) for secure and energy-efficient routing in WSNs. The approach involves a two-phase process: initially, the Kookaburra Adapted Pufferfish Optimization Algorithm (KAPOA) algorithm is used for optimal Cluster Head (CH) selection. KAPOA is a hybrid of the Pufferfish Optimization Algorithm (POA) and the Kookaburra Optimization Algorithm (KOA). It enhances the conventional POA by incorporating a specific modification from the KOA and assigning weights to improve performance. This algorithm selects optimal CHs in accordance with factors including delay, risk, energy consumption, trust, and distance. In the subsequent phase, the Dijkstra algorithm is employed to determine the shortest path for energy-efficient data transmission. The final phase integrates the Improved Advanced Encryption Standard (IAES), an enhanced version of the conventional Advanced Encryption Standard (AES), to ensure secure data transmission. The efficiency of this approach is evaluated through comparative analyses with existing methods. This integrated strategy effectively tackles the dual challenges of security and energy efficiency in WSN environments. The KAPOA method achieves a delay of 0.142&#xa0;s, with a moderate risk of 0.452 and energy consumption of 0.465&#xa0;J, while maintaining a high Packet Delivery Ratio (PDR) of 93.66% and leaving a residual energy of 0.274&#xa0;J.</p>

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Secure-energy efficient hybrid optimal cluster-based routing with improved AES in WSN for secure data transmission

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月3日

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  • Dr.Gowdham C,
  • Dr.John Deva Prasanna D S,
  • Arun Anthonisamy A

摘要

Wireless Sensor Networks (WSNs) encounter significant issues in managing both security and energy efficiency due to the limitations of current solutions. The high energy consumption associated with secure data transmission often leads to rapid battery depletion in Sensor Nodes (SNs), compromising the network's overall longevity and performance. Furthermore, existing methods often overlook critical factors such as network delay, data integrity, SNs trust, and potential security breaches. To address these issues, this research proposes a novel KAPOA-IAES-based routing approach (KAPOA-IAES) for secure and energy-efficient routing in WSNs. The approach involves a two-phase process: initially, the Kookaburra Adapted Pufferfish Optimization Algorithm (KAPOA) algorithm is used for optimal Cluster Head (CH) selection. KAPOA is a hybrid of the Pufferfish Optimization Algorithm (POA) and the Kookaburra Optimization Algorithm (KOA). It enhances the conventional POA by incorporating a specific modification from the KOA and assigning weights to improve performance. This algorithm selects optimal CHs in accordance with factors including delay, risk, energy consumption, trust, and distance. In the subsequent phase, the Dijkstra algorithm is employed to determine the shortest path for energy-efficient data transmission. The final phase integrates the Improved Advanced Encryption Standard (IAES), an enhanced version of the conventional Advanced Encryption Standard (AES), to ensure secure data transmission. The efficiency of this approach is evaluated through comparative analyses with existing methods. This integrated strategy effectively tackles the dual challenges of security and energy efficiency in WSN environments. The KAPOA method achieves a delay of 0.142 s, with a moderate risk of 0.452 and energy consumption of 0.465 J, while maintaining a high Packet Delivery Ratio (PDR) of 93.66% and leaving a residual energy of 0.274 J.