Security Control of Safety-Critical Systems.

Area of Science:

• Control Theory
• Cyber-Physical Systems Security
• Nonlinear Systems

Background:

• Safety-critical systems face vulnerabilities from denial-of-service (DoS) attacks.
• Ensuring system integrity under adversarial conditions is crucial for applications like autonomous vehicles and critical infrastructure.
• Existing control strategies may not adequately address the dual challenge of safety and security under dynamic constraints.

Purpose of the Study:

• To develop an integrated security and safety-critical control law for nonlinear uncertain systems.
• To mitigate the impact of DoS attacks on signal transmission channels.
• To guarantee collision avoidance and internal dynamic limitations are maintained.

Main Methods:

• An improved dynamic compensator is proposed using the internal model principle and hybrid time/event-triggered sampling for DoS detection.
• The safety tracking problem is reformulated as an attractivity problem of a constrained error system.
• A security control is designed within a barrier function framework, integrating the safety-critical controller.

Main Results:

• The proposed integrated control law effectively prevents unsafe system operation during DoS attacks.
• The dynamic compensator successfully detects DoS attacks by analyzing system behavior.
• The barrier function-based framework ensures the error system remains attractive and constrained.

Conclusions:

• The integrated security and safety-critical control design guarantees the closed-loop system's security, safety, and stability.
• This approach provides a robust solution for protecting safety-critical systems against sophisticated cyber threats.
• The findings have significant implications for the reliable operation of autonomous and networked systems.