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Improving Attack Detection Accuracy in Goose Protocol Networks in Smart Grids Using Random Forest Algorithm

Authors :

Mohsen Attari¹ Seyed reza Kamel² Reza Sheibani³

1- دانشگاه آزاد اسلامی واحد مشهد 2- دانشگاه آزاد اسلامی واحد مشهد 3- دانشگاه آزاد اسلامی واحد مشهد

Keywords :

IDS،IEC61850،Goose،Random Forest،machine learning

Abstract :

This paper presents a novel method to enhance attack detection in Goose protocol networks. By incorporating momentary electrical parameters of power substations into machine learning algorithms, we increase the accuracy of attack detection and equip the IDS system with the capability to identify the type of attack. Additionally, we provide a model utilizing two different machine-learning engines to enhance early-stage attack detection for IPS system triggering.

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