Enhanced stochastic coding framework for discriminating faults and cyber incidents in hybrid systems

Abstract

This article presents an innovative approach for distinguishing replay attacks from faults in hybrid systems. To develop the idea at first, a novel technique for replay attack detection, which differentiates it from typical system faults, is introduced. This is achieved through a tactical combination of stochastic coding and a window-based comparison mechanism, setting a new standard in hybrid system security. In the realm of fault detection, robust L₂-L_∞ adaptive observers are employed for precise mode detection, allowing for an accurate assessment of the system's operational state. Additionally, robust H_∞ Sliding Mode Observers are utilized to identify abnormal behaviours in the system's output, further solidifying the fault detection capabilities. A significant enhancement in the proposed approach is the integration of a Luenberger observer with the Butterworth low-pass filter. This novel addition not only refines the filtering process but also contributes to the overall reliability and accuracy of the system. The efficiency and versatility of these methods are demonstrated through their application to a four-tank hybrid system. This practical simulation showcases the adaptability of the approach to real-world scenarios, highlighting its potential in diverse applications within the field of hybrid systems.