<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The Internet of Things, as an important part of important data aggregation, forwarding and control, is often subject to risks such as eavesdropping or data loss due to the huge amount of received data. Based on this, this paper introduces the GA-LM-BP algorithm, BP network, and LM-BP algorithm deep learning to optimize the data received by the Internet of Things, and selects the most suitable communication mode optimization algorithm. The experimental results show that the accuracy error of GA-LM-BP, BP and LM-BP algorithms shows a downward trend, from 0.029 to 0.011; the training time is reduced by 208 mins, and the training speed is increased to 74%, indicating that GA-LM-BP deep learning Excellent performance in the security and confidentiality of data transmission in the Internet of Things. In addition, we further analyzed GA-LM-BP from COP, SOP and STP to verify its reliability and safety.</p>
</abstract>

The Internet of Things, as an important part of important data aggregation, forwarding and control, is often subject to risks such as eavesdropping or data loss due to the huge amount of received data. Based on this, this paper introduces the GA-LM-BP algorithm, BP network, and LM-BP algorithm deep learning to optimize the data received by the Internet of Things, and selects the most suitable communication mode optimization algorithm. The experimental results show that the accuracy error of GA-LM-BP, BP and LM-BP algorithms shows a downward trend, from 0.029 to 0.011; the training time is reduced by 208 mins, and the training speed is increased to 74%, indicating that GA-LM-BP deep learning Excellent performance in the security and confidentiality of data transmission in the Internet of Things. In addition, we further analyzed GA-LM-BP from COP, SOP and STP to verify its reliability and safety.

Secure transmission of wireless energy-carrying communication systems for the Internet of Things

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

The Internet of Things, as an important part of important data aggregation, forwarding and control, is often subject to risks such as eavesdropping or data...

Secure transmission of wireless energy-carrying communication systems for the Internet of Things

Online veröffentlicht: 28. Apr. 2023

Seitenbereich: 3135 - 3148

Eingereicht: 17. März 2022

Akzeptiert: 05. Juli 2022

DOI: https://doi.org/10.2478/amns.2023.1.00026

Schlüsselwörter
Wireless communication system, Secure transmission, GA-LM-BP, BP, LM-BP

© 2023 Gang Zhou et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Secure transmission of wireless energy-carrying communication systems for the Internet of Things

Online veröffentlicht: 28. Apr. 2023

Seitenbereich: 3135 - 3148

Eingereicht: 17. März 2022

Akzeptiert: 05. Juli 2022

DOI: https://doi.org/10.2478/amns.2023.1.00026

SchlüsselwörterWireless communication system, Secure transmission, GA-LM-BP, BP, LM-BP

© 2023 Gang Zhou et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Wireless communication system, Secure transmission, GA-LM-BP, BP, LM-BP