CNNs Model for Cyber Threat Detection in Advanced Metering Infrastructure for Securing the Smart Grid

The modernization of electrical grids is becoming more dependent on the adoption of Advanced Metering Infrastructure (AMI), which is becoming an important component. Because of this there is an increase in the number of connections, which in turn leads to the emergence of new problems, particularly in the area of cybersecurity. The purpose of this research is to address the pressing need for trustworthy cyber threat detection methods within the framework of smart grids, with a specific focus on the Advanced Metering Infrastructure. The model that has been developed provides a fresh approach to the challenge of recognizing and mitigating cyber threats that are targeted at the AMI. This is because the model incorporates a novel approach to the problem. To accomplish this goal, the capabilities of Convolutional Neural Networks (CNNs) give the tools by which it may be accomplished.