Security Attacks on Smart Grid Scheduling and Their Defences: A Game-Theoretic Approach
This addresses security vulnerabilities in smart grids for utility companies, though it is incremental as it builds on existing game-theoretic methods.
The paper identifies a new class of false data injection attacks on smart grid energy management by manipulating forecasted demand data, and proposes game-theoretic monitoring strategies to detect them and allocate defense resources, revealing Nash Equilibrium strategies.
The introduction of advanced communication infrastructure into the power grid raises a plethora of new opportunities to tackle climate change. This paper is concerned with the security of energy management systems which are expected to be implemented in the future smart grid. The existence of a novel class of false data injection attacks that are based on modifying forecasted demand data is demonstrated, and the impact of the attacks on a typical system's parameters is identified, using a simulated scenario. Monitoring strategies that the utility company may employ in order to detect the attacks are proposed and a game--theoretic approach is used to support the utility company's decision--making process for the allocation of their defence resources. Informed by these findings, a generic security game is devised and solved, revealing the existence of several Nash Equilibrium strategies. The practical outcomes of these results for the utility company are discussed in detail and a proposal is made, suggesting how the generic model may be applied to other scenarios.