Researchers are exploring various methods for detecting distributed denial-of-service attacks in internet of things (IoT) networks, including ensemble-based detection and machine learning approaches. These methods involve feature fusion, selection, and pruning to efficiently identify potential threats. Different frameworks and algorithms, such as deep learning and hybrid feature selection, are being developed and tested for their effectiveness in detecting DDoS attacks in IoT environments.