Distributed H_∞ Estimation in Sensor Networks With Two-Channel Stochastic Attacks

Area of Science:

• Control Systems Engineering
• Network Security
• Signal Processing

Background:

• Sensor networks are vulnerable to unknown attacks on communication channels.
• Attacks can disrupt data transmission between plants, sensors, and among sensors.
• Stochastic attack models are crucial for realistic network security analysis.

Purpose of the Study:

• To develop a novel distributed estimation model for sensor networks under two-channel stochastic attacks.
• To ensure robust and reliable state estimation in the presence of unknown network intrusions.
• To design effective distributed H_∞ estimators for enhanced network security.

Main Methods:

• A new distributed estimation model is proposed, integrating sensor measurements and neighbor information.
• The study derives a sufficient condition for the existence of distributed H_∞ estimators.
• Distributed estimator gains are designed by solving linear matrix inequalities (LMIs).

Main Results:

• A novel distributed estimation framework is presented to counter two-channel stochastic attacks.
• A condition for the existence of the proposed distributed H_∞ estimators is established.
• The effectiveness of the design techniques is validated through two illustrative examples.

Conclusions:

• The proposed distributed estimation approach effectively addresses stochastic attacks in sensor networks.
• The developed H_∞ estimators provide a robust solution for secure distributed estimation.
• The LMI-based design offers a practical method for implementing secure sensor networks.