Secure impulsive tracking of multi-agent systems with directed hypergraph topologies against hybrid deception attacks

Area of Science:

• Control Theory
• Networked Systems
• Cybersecurity

Background:

• Multi-agent systems (MAS) face challenges in achieving secure consensus tracking.
• Directed hypergraph topologies introduce complexity in MAS communication.
• Hybrid deception attacks pose significant threats to system integrity.

Purpose of the Study:

• To develop a robust control strategy for secure consensus tracking in MAS with directed hypergraph topologies.
• To address hybrid discrete and continuous deception attacks targeting controllers and hyperedges.
• To establish conditions for maintaining mean-square bounded consensus under adversarial conditions.

Main Methods:

• Utilizing hypergraph theory to design an impulsive control mechanism.
• Developing rigorous mathematical proofs to establish sufficient conditions for consensus.
• Quantifying the relationship between consensus error and deception attack intensity.

Main Results:

• Sufficient conditions for mean-square bounded consensus were established under hybrid attacks.
• A specific range for the consensus error metric relative to attack intensity was delineated.
• The proposed impulsive control mechanism demonstrated robustness and effectiveness in simulations.

Conclusions:

• Hypergraph-based impulsive control offers a viable strategy for enhancing MAS resilience against complex hybrid attacks.
• The findings provide a theoretical framework and practical validation for secure consensus in adversarial networked systems.
• This research contributes to the advancement of secure and robust control strategies for distributed systems.