Detection and Classification of DoS Attacks in Zigbee Networks Using Supervised Learning Algorithms

The Zigbee protocol, designed for low-power wireless personal area networks, is a key technology for the Internet of Things (IoT). This paper explores detect- ing denial-of-service (DoS) attacks in Zigbee networks through supervised clas- sification methods. A specialized dataset was generated from a simulated Zigbee environment, capturing both normal and malicious traffic. The study evaluates the effectiveness of six supervised classification algorithms, including Logistic

Authors

• Jose Aveleira Mata
• Míriam Timiaos
• María Teresa García-Ordás
• Marta-María Álvarez-Crespo
• Esteban Jove
• Héctor Alaiz-Moretón

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