This study deals with the research of DDoS attacks on IoT devices and the importance of high quality datasets for effective detection of these attacks. A specialized dataset was created using an ESP8266 IoT device. The dataset contains various types of DDoS attacks, including TCP SYN flood, ICMP flood, Slowloris, Slow post, and UDP flood. The dataset was constructed to simulate real-world conditions and provide accurate and representative data for analysis and development of advanced detection mechanisms. The results show that different types of attacks have different impacts on the availability and functionality of IoT devices, highlighting the need for diverse and up-to-date datasets in the field of IoT cybersecurity. This work contributes to a deeper understanding of the dynamics of DDoS attacks on IoT infrastructure and provides a suitable tool for future research and development of detection technologies.