A Tri-level Programming Framework for Modelling Attacks and Defences in Cyber-Physical Systems.

Smart power grids suffer from coordinated attacks that exploit both their physical and cyber layers. It is an inevitable requirement to study power systems under such complex hacking scenarios to discover the system vulnerabilities and protect against those vulnerabilities and their attack vectors with appropriate defensive actions. This paper proposes an efficient tri-level programming framework that dynamically determines attacking scenarios, along with the best defensive actions in cyber-physical systems. A tri-level optimisation framework is proposed to fit the optimal decisions of defence strategies, malicious vectors and their operators for optimising the unmet demand while launching hacking behaviours. Defending resource allocation is designed using an evolutionary algorithm to examine coordinated attacks that exploit power systems. The proposed framework includes a Genetic Algorithm (GA) to solve each of the model levels in power systems. This proposed framework can flexibly model malicious vectors and their defences. IEEE 14-bus benchmark is employed to evaluate the proposed framework.