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

• Autores: Gang Zhou, Mingyang Peng, Yan Li, Jian Wang, Wei-Cheng Lian
• Localización: Applied Mathematics and Nonlinear Sciences, ISSN-e 2444-8656, Vol. 8, Nº. 1, 2023, págs. 3135-3148
• Idioma: inglés
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• Resumen

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