doi.org
IoT Attacks Detection Using Supervised Machine Learning Techniques
September 2024 • Malak Aljabri, Afrah Shaahid, Fatima Alnasser, Asalah Saleh, Dorieh M. Alomari, Menna Aboulnour, Walla Al-Eidarous, Areej Althubaity
In recent times, the growing significance of Internet of Things (IoT) devices in people's lives is undeniable, driven by their myriad benefits. However, these devices confront cybersecurity threats akin to traditional network devices, as they depend on networks for connectivity and synchronization. Artificial Intelligence (AI) techniques, specifically Machine Learning (ML) and Deep Learning (DL), have demonstrated notable reliability in the field of cyberattack detection. This study focuses on detecting Flood and …