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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Cybersecurity

Background:

  • Intelligent Transport Systems (ITS), an advanced form of Vehicle Ad-hoc Networks (VANET), enhance traffic management.
  • Integrating the Internet of Things (IoT) with ITS creates connected and cooperative automated mobility (IoT-ITS).
  • IoT-ITS development faces significant challenges due to data security and privacy risks.

Purpose of the Study:

  • To propose a secure IoT-ITS framework addressing critical security demands and risk factors.
  • To leverage cognitive science for enhanced security in connected transport environments.
  • To differentiate legitimate users from malicious actors within the IoT-ITS framework.

Main Methods:

  • A detailed risk analysis of the IoT-ITS environment was conducted.
  • Cognitive science principles were applied to design a robust security framework.
  • Real-time data analysis was performed using cognitive science techniques.

Main Results:

  • The proposed cognitive science-based framework effectively resolves security demands.
  • The framework successfully mitigates associated risk factors without compromising functionality.
  • Experimental results demonstrate improved security and data analysis capabilities.

Conclusions:

  • Cognitive science offers a viable solution for securing IoT-ITS.
  • The developed framework enhances the safety and privacy of automated mobility systems.
  • This approach provides a foundation for more secure and intelligent transportation in the future.