LATAM-DDoS-IoT dataset

Intrusion Detection Systems based on Artificial Intelligence need robust data sources in order to achieve strong generalization levels from the knowledge domain of interest. Anomaly detection is a well-known topic in cybersecurity, and its application to the Internet of Things can lead to suitable protection techniques against problems such as DoS and DDoS attacks. Here we present the creation of a new dataset called LATAM-DDoS-IoT, result of a collaboration between Aligo, Universidad de Antioquia, and Tecnologico de Monterrey, that includes attack traffic to physical Internet of Things devices, and normal traffic from external real users consuming real services from Aligo's production network. These characteristics make our dataset be convenient for real production environments.