Blockchain-Assisted Intelligent Resilient Tracking Control of Networked Systems

Area of Science:

• Control Systems Engineering
• Cybersecurity
• Blockchain Technology

Background:

• Networked Control Systems (NCSs) face significant security challenges due to increasing integration.
• Existing resilient control methods require further development for advanced threats like smart False Data Injection (FDI) attacks.

Purpose of the Study:

• To design and analyze a security control strategy for NCSs vulnerable to FDI attacks.
• To enhance the security and performance of NCSs using blockchain technology and game theory.

Main Methods:

• Utilized peer-to-peer (P2P) networks with blockchain for secure signal transmission.
• Developed an optimal blockchain consensus policy derived from a game-theoretic framework.
• Designed a resilient dynamic output tracking controller based on the consensus policy.

Main Results:

• Successfully mitigated the adverse effects of malicious FDI attacks.
• Achieved a balance between energy consumption and tracking performance.
• Demonstrated the strategy's applicability in a real-world power system.

Conclusions:

• The proposed security control strategy effectively enhances NCS security against FDI attacks.
• The integration of blockchain and game theory offers a robust defense mechanism.
• The approach is validated for practical implementation in critical infrastructure like power systems.