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Updated: Dec 22, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

997

Realizing Efficient Security and Privacy in IoT Networks.

Joseph Henry Anajemba1, Yue Tang1, Celestine Iwendi2

  • 1Department of Communication Engineering, College of Internet of Things, Hohai University, Nanjing 210098, China.

Sensors (Basel, Switzerland)
|May 8, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces efficient algorithms to enhance physical layer (PHY) security in wireless networks, addressing challenges in the Internet of Things (IoT) and 5G cellular systems. The proposed methods optimize transmission parameters for improved security and privacy against eavesdroppers.

Keywords:
5GIoTMIMOMEjammingphysical layer securityprivacy capacity

Related Experiment Videos

Last Updated: Dec 22, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

997

Area of Science:

  • Wireless Communication Security
  • Physical Layer Security
  • Network Optimization

Background:

  • Physical layer (PHY) security is critical for emerging technologies like the Internet of Things (IoT) and 5G cellular networks.
  • A key challenge is the lack of information about passive eavesdroppers, hindering optimization of communication parameters.
  • Existing security measures often struggle with complex network scenarios involving multiple eavesdroppers.

Purpose of the Study:

  • To propose an efficient sequential convex estimation optimization (SCEO) algorithm for enhancing PHY security in a three-node wireless network.
  • To develop a swift privacy rate optimization algorithm for multiple-input, multiple-output, multiple-eavesdropper (MIMOME) scenarios relevant to IoT and 5G.
  • To improve security and privacy by optimizing broadcasting parameters and managing self-interference.

Main Methods:

  • Developed a sequential convex estimation optimization (SCEO) algorithm for a three-node wireless network.
  • Designed a privacy rate optimization algorithm for multiple-input, multiple-output, multiple-eavesdropper (MIMOME) systems.
  • Incorporated rate constraints and self-interference management for full-duplex transmission.

Main Results:

  • The SCEO algorithm demonstrated optimal performance and enhanced convergence in transmissions.
  • The privacy rate optimization algorithm for MIMOME scenarios showed significant execution with minimal complexity.
  • The combined techniques resulted in outstanding performance compared to previous studies.

Conclusions:

  • The proposed algorithms effectively enhance physical layer security and privacy in wireless communication networks.
  • The methods are particularly beneficial for securing IoT and 5G environments against eavesdropping.
  • The optimization strategies offer a robust solution for complex network conditions with multiple eavesdroppers.