A quantum-based approach for offensive security against cyber attacks in electrical infrastructure

Deciding the correct offensive security strategy for safeguarding the electrical physical infrastructures of smart grids is a challenging task. The offensive security training against various cyber-attacks focuses on a multitude of electrical subsystems and measurement systems like the Load Frequency Control(LFC) system. Primarily, the principal challenge is to categorize and parameterize the various possible cyber-attacks on electrical infrastructures. This is done by specifying and selecting cyber-attacks considering various main and subsystem blocks of the power structural system within each area of major installations. In this research investigation, formal modeling of security strategy is proposed using Lambda calculus with both classical and quantum perspectives. Furthermore, using a Quantum Machine Learning (QML) technique, the procedure for correct vulnerability prediction, exploitation, and execution strategy is presented with an approximated likelihood of attack and its mode. The local and non-local interactions are introduced as quantum threats and entanglement threats similar to False Data Injection (FDI) methods to induce the attack and counter-attack events through quantum causality connections. Finally, the Quirk simulator is used to validate the proposed quantum design of offensive and defensive attack models considering scenarios of exogenous and scaling attacks on the LFC systems that support the feasibility of the present research work to address the issue of cyber-attacks on the power system networks.