Proactive Threat Hunting in Critical Infrastructure Protection through Hybrid Machine Learning Algorithm Application

Proactive Threat Hunting in Critical Infrastructure Protection through Hybrid Machine Learning Algorithm Application

Cyber-security challenges are growing globally and are specifically targeting critical infrastructure. Conventional countermeasure practices are insufficient to provide proactive threat hunting. In this study, random forest (RF), support vector machine (SVM), multi-layer perceptron (MLP), AdaBoost,...

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Bibliographic Details
Main Authors: Ali Shan, Seunghwan Myeong
Format: Article
Language:English
Published: MDPI AG 2024-07-01
Series:Sensors
Subjects:
cyber-attacks
threats
machine learning
cyber-security
Online Access:https://www.mdpi.com/1424-8220/24/15/4888

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https://www.mdpi.com/1424-8220/24/15/4888

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