Secure Grid-AI

Abstract

SecureGrid-AI is an architectural framework that introduces a new machine learning algorithm paired with an automated alerting system to detect and mitigate Denial of Service (DoS) and other advanced cyberattacks in smart grid environments. The design targets a key vulnerability in smart grids that arises from increasing digitalization. Current smart grid security largely relies on manual or rule-based intrusion detection systems (IDS), which struggle to identify previously unseen threats, such as zero-day attacks, due to their dependence on predefined signatures. This limitation often leads to high false-negative rates and slow response times.To address these challenges, SecureGrid-AI adopts a multi-layered machine learning approach. The system analyzes network traffic in real time using algorithms such as Decision Trees and Random Forests to directly classify and identify different types of cyberattacks with greater accuracy and responsiveness.