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6G -enabled qubit-based concealed communication with AI-driven breach detection in autonomous fleets.

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Summary

This study introduces a Secure Module for Concealed Navigation Communication (SM-CNC) for autonomous vehicles. The module enhances security by using quantum computing and recurrent learning, improving authentication rates and reducing communication failures.

Keywords:
Autonomous vehiclesCommunication authenticationQuantum computingRecurrent learningSecure navigation

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Area of Science:

  • Cybersecurity
  • Quantum Computing
  • Artificial Intelligence

Background:

  • Autonomous vehicles (AVs) require secure communication channels for navigation and data exchange.
  • Current communication methods face challenges with complex computations and potential security breaches in heterogeneous environments.
  • Secure information exchange is crucial for AVs to ensure precise navigation, object detection, and reliable data transmission.

Purpose of the Study:

  • To introduce a novel Secure Module for Concealed Navigation Communication (SM-CNC) designed for autonomous vehicle environments.
  • To enhance the security and reliability of communication in AVs by addressing complex computations and interception risks.
  • To leverage quantum computing and recurrent learning for secure and efficient information exchange.

Main Methods:

  • The proposed SM-CNC module utilizes volatile authentication that disintegrates upon interception.
  • Information is dropped if unauthorized vehicles intercept, with monitoring during relaying and validation.
  • The module employs quantum computing, modeling information points as qubits, and recurrent learning for security and reliable communication.

Main Results:

  • The SM-CNC module demonstrated a 9.29% improvement in authentication rate.
  • Communication failure was reduced by 11.87%.
  • Computation complexity was reduced by 12.13% for maximum communication requests per interval.

Conclusions:

  • The proposed SM-CNC module significantly enhances communication security and reliability in autonomous vehicles.
  • The integration of quantum computing and recurrent learning provides a robust solution against security breaches and unauthorized access.
  • SM-CNC offers improved performance metrics, making AV communications more secure and efficient.