Design of Relaxed Greedy Approach based Threat Detection Framework for Smart Grid Systems

Abstract

Cyber-attacks represent a huge danger to Smart Grid infrastructure, causing
substantial interruptions in electricity supply as well as severe economic and
social consequences. As a result, there is a need for an efficient and effective threat detection mechanism for security of the Smart Grid infrastructure.
In this research, we offer a design for a threat detection system based on the
Relaxed Greedy Method for Smart Grid architecture. The suggested framework is based on the Relaxed Greedy algorithm, a heuristic-based technique to
optimising problems. This approach is well-known for its efficiency, efficacy,
and simplicity in tackling large-scale optimization problems to detect possible
dangers in the Smart Grid infrastructure based on the collected attributes. The
suggested system is tested using a real-world dataset taken from a Smart Grid
testbed. The experimental findings suggest that the proposed framework can
identify various forms of threat detections in the Smart Grid infrastructure.