A secured IoT-based intelligent transport system (IoT-ITS) framework based on cognitive science

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.