Secure Networking with Software-Defined Reconfigurable Intelligent Surfaces

Area of Science:

• Wireless Communications
• Network Security
• Information Theory

Background:

• Reconfigurable intelligent surfaces (RIS) are crucial for advancing 6G air-ground and THz communications.
• RIS offer enhanced Physical Layer Security (PLS) by controlling signal reflections to improve secrecy capacity and mitigate eavesdropping.
• Existing network architectures lack integrated control for secure data flow management using multi-RIS systems.

Purpose of the Study:

• To propose and evaluate a Software Defined Networking (SDN) architecture for integrated control of multi-RIS systems.
• To optimize secure data flow forwarding in 6G networks utilizing multi-RIS.
• To analyze the impact of multi-RIS deployment on Physical Layer Security (PLS) performance.

Main Methods:

• Characterization of an optimization problem with a defined objective function for secure data routing.
• Application of graph theory to model and find optimal solutions for multi-RIS deployment.
• Development and evaluation of heuristic algorithms to balance complexity and PLS performance for multi-beam routing.
• Numerical simulations focusing on worst-case scenarios and user mobility patterns.

Main Results:

• The proposed SDN-integrated multi-RIS system significantly improves secrecy rates, particularly as the number of eavesdroppers increases.
• Heuristic strategies effectively balance computational complexity with achieved PLS performance.
• The system demonstrates robust security performance under specific user mobility conditions in pedestrian scenarios.

Conclusions:

• The integration of multi-RIS within an SDN architecture provides an effective control layer for enhancing secure data flows in 6G networks.
• The proposed optimization and heuristic approaches offer practical solutions for deploying RIS to bolster Physical Layer Security.
• This framework demonstrates the potential of RIS in future wireless systems to achieve higher levels of security and performance.