Secure Adaptive-Event-Triggered Filter Design With Input Constraint and Hybrid Cyber Attack.

Area of Science:

• Control Systems Engineering
• Cybersecurity
• Signal Processing

Background:

• Secure filter design is crucial for systems facing sophisticated cyber threats.
• Event-triggered schemes aim to reduce communication load in control systems.
• Hybrid cyber attacks combine multiple attack vectors, posing complex challenges.

Purpose of the Study:

• To develop a secure adaptive-event-triggered filter design robust to hybrid cyber attacks.
• To address input constraints within the filter design framework.
• To enhance communication efficiency using an adaptive event-triggered mechanism.

Main Methods:

• A novel hybrid cyber attack model integrating deception, replay, and denial-of-service (DoS) attacks.
• An adaptive event-triggered scheme for resource-constrained communication.
• Development of an adaptive-event-triggered filtering error model considering attacks and input constraints.
• Application of Lyapunov stability theory and linear matrix inequality (LMI) techniques.

Main Results:

• Sufficient conditions derived to guarantee the stability of the augmented system.
• Explicit formulas provided for the parameters of the designed filter.
• Validation of the proposed method through simulation examples.

Conclusions:

• The proposed adaptive-event-triggered filter design effectively enhances system security against hybrid cyber attacks.
• The method optimizes communication resource usage while maintaining system stability.
• The explicit filter parameter derivation facilitates practical implementation.