Secure Fusion Estimation of Energy-Constrained Multisensor System Against Hybrid Attacks

Area of Science:

• Cyber-Physical Systems
• Information Fusion
• Sensor Networks

Background:

• Energy constraints in sensor nodes limit operational lifespan.
• Dual-energy transmission modes (high/low) impact data accuracy and security.
• Multisensor systems are vulnerable to hybrid attacks (deception, DoS) at different transmission levels.

Purpose of the Study:

• To develop a theoretical framework for secure fusion estimation in energy-constrained multisensor systems.
• To address hybrid attacks in systems with dual-energy transmission capabilities.
• To enhance the robustness and reliability of data fusion under adversarial conditions.

Main Methods:

• A novel measurement model using Bernoulli and ternary random variables to characterize dual-energy modes and hybrid attacks.
• Innovation analysis approach to design local secure estimators minimizing estimation errors.
• An optimal secure fusion algorithm to integrate local estimates for a final fused value.

Main Results:

• The proposed framework effectively minimizes local estimation errors.
• The optimal secure fusion algorithm provides a reliable final estimate.
• Stability and steady-state properties of the fusion algorithm are rigorously investigated.
• Simulations demonstrate superior performance compared to existing methods.

Conclusions:

• The developed secure fusion estimation framework enhances system security and data integrity.
• The approach is effective in mitigating hybrid attacks in energy-constrained multisensor systems.
• The proposed method offers a robust solution for reliable information fusion.