In this book chapter, the focus is on analyzing and evaluating datasets commonly used in Intrusion Detection Systems for IoT security. Given the complex networks formed by interconnected devices, the chapter emphasizes the critical role of effective data analysis and attack detection in enhancing IoT system security. Through a multifaceted examination, the study identifies key features and pre-processing requirements of datasets that contribute to improved model performance. Additionally, it investigates the diversity of attack types within these datasets, aiding researchers in selecting the most appropriate datasets for specific scenarios. By conducting comparative analyses, the chapter aims to highlight the most suitable datasets for IoT IDS systems, contributing valuable insights to the field of cybersecurity.