The development of information technologies makes significant contributions to various aspects of our life. It brings various innovations together, depending on the rate of technology's growth. The Internet of Things (IoT) is among the most popular and fastest expanding technologies in recent years. Addressable IoT devices generate and use significant data over the Internet. Because of the increase in data traffic, attacks in IoT networks are also increasing significantly.The present book increases security in IoT communication by providing binary and multi-label classification methods for identifying attacks in IoT networks. A new Hybrid Deep Learning model has been designed for detecting intrusions. The successful performance of our proposed model is proof that hybrid Deep Learning methods can be an innovative and efficient perspective in IoT Intrusion Detection Systems.