This paper outlines emerging security strategies and frameworks, focusing on taxonomies designed to categorize aspects of cybersecurity, particularly IoT security incidents, including threats and attacks. A comparative analysis of the TON_IoT, Edge-IIoTset, and CICIoT2023 datasets is presented, examining their classifications of IoT threats and attacks. Additionally, the ENISA Taxonomy adopted by INCIBE-CERT CSIRT is reviewed and compared with the taxonomies of NIST CSF 2.0, MITRE ATT&CK, and OWASP, which incorporates STRIDE. Next, the taxonomies of the TON_IoT, Edge-IIoTset, and CICIoT2023 datasets are mapped to the ENISA and INCIBE Taxonomy, correlating the categories of cyber threats and attacks identified in each dataset with these classification systems. Aiming to enhance AI-driven solutions for IoT cybersecurity, this study underscores both the similarities and differences in the number and names of categories of threats and attacks, and in the labels assigned to these incidents across the analyzed taxonomies and datasets.