The explosure of IoT devices and data generated by the devices are increasing rapidly. IoT devices are becoming susceptible to cyberattacks and data breaches, which leads to new security and privacy issues. Frequent network maintenance, intrusion detection, access control, authentication, and encryption should be considered, and security measures should be taken on time to secure IoT. I.D.S. are significant since they alert network administrator when unusual activity occurs. Recent research in the field of I.D.S., benefits and drawbacks, different categories like anomaly-based, signature base, cloud and hybrid-based. New trends in I.D.S. in IoT networks are the main highlights of this chapter, such as Explainable AI (XAI), Context-aware AI, Transfer Learning, Neuro-symbolic AI, and Artificial Intelligence (AI). The practical examples and case studies discussed in the chapter will give a better understanding of how IDS is applied in several IoT and related fields. The assessment of the performance of the IDS systems is measured in different ways, and the metrics are discussed thoroughly, along with several datasets used for the IDS implementation in IoT Networks. Readers such as professionals, scholars, and individuals interested in cybersecurity and IoT will be able to choose the appropriate IDS system for an IoT network based on their requirements. The future of the IDS system is explored, as well as its pros and cons. Since this chapter is equipped with recent trends and up-to-date information, beginners and specialists in this field may find it appropriate for their area of interest.