Quickest Bayesian and non-Bayesian detection of false data injection attack in remote state estimation

Key Points

• Detection of false data injection attacks significantly improves with both Bayesian and non-Bayesian approaches, ensuring robust performance.
• Key metrics show the Bayesian method provides faster detection times compared to non-Bayesian, enhancing response times to threats.
• Study utilizes a comparative analysis of detection algorithms across simulated environments to assess effectiveness against varied attack scenarios.
• Findings highlight the urgent need for advanced detection methods, as current systems remain vulnerable to data injection strategies.