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<p>To date, the development of the Internet of Things (IoT) is a significant source in several applications, including Wireless Sensor Network (WSN). However, the maximization of the network lifetime is the major concern. Also, none of the prevailing works focused on attack prediction in SCH, thus affecting the network longevity. Therefore, this paper proposes a Deep-SHC-ADRNN and LFHIS-based CH selection and secure IoT communication in a 6G WSN-assisted smart city. Primarily, the WSN nodes are optimally deployed in the monitoring area using A-TDO. Now, the network expiry time is predicted through LFHIS.Likewise, the node factors are estimated to select the CH and SCH based on LFHIS. Subsequently, the attack detection is done based on the proposed Deep-SHC-ADRNN classifier, which classifies whether the SCH is attacked or not. Next, the double cluster is formed via B2C-HC. Afterward, the IoT data is sensed from the smart city and then the dimensionality of the data is reduced using 2SP-PCA. Also, the data is encrypted via MC25519-C, followed by optimal path identification. Finally, the data is transmitted to the end-user via NB-IoT protocol. Thus, the experimental results showed that the proposed approach had higher dominance with 98.97% accuracy. </p>

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SCH-Enabled Deep-SHC-ADRNN and LFHIS-Based CH Selection and Secure IoT Communication in 6G WSN-Assisted Smart City

  • 期刊论文

  • 发表日期：

    2025年5月8日

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  • Hemantaraj M. Kelagadi,
  • M. R. Prasad,
  • B. T. Ramesh

摘要

To date, the development of the Internet of Things (IoT) is a significant source in several applications, including Wireless Sensor Network (WSN). However, the maximization of the network lifetime is the major concern. Also, none of the prevailing works focused on attack prediction in SCH, thus affecting the network longevity. Therefore, this paper proposes a Deep-SHC-ADRNN and LFHIS-based CH selection and secure IoT communication in a 6G WSN-assisted smart city. Primarily, the WSN nodes are optimally deployed in the monitoring area using A-TDO. Now, the network expiry time is predicted through LFHIS.Likewise, the node factors are estimated to select the CH and SCH based on LFHIS. Subsequently, the attack detection is done based on the proposed Deep-SHC-ADRNN classifier, which classifies whether the SCH is attacked or not. Next, the double cluster is formed via B2C-HC. Afterward, the IoT data is sensed from the smart city and then the dimensionality of the data is reduced using 2SP-PCA. Also, the data is encrypted via MC25519-C, followed by optimal path identification. Finally, the data is transmitted to the end-user via NB-IoT protocol. Thus, the experimental results showed that the proposed approach had higher dominance with 98.97% accuracy.