A Systematic Review of Intrusion Detection Systems in Internet of Things Using ML and DL

The rapid expansion of IoT technologies like smart sensors and home appliances is likely to have far-reaching consequences. Connectivity, ubiquitous presence, and low computational power are the hallmarks of IoT gadgets. The global tally of Internet of Things gadgets is on the rise. There has been an increase in IoT -based cyber-attack incidents due to the proliferation of these devices, which is much easier to do than with desktop computers. New methods of identifying attacks launched from compromised IoT devices are needed to help address this issue. In this scenario, the most effective method of detective control against attacks originating from IoT devices is the application of ML and DL techniques. The main aim of this research is to provide an overview of intrusion detection models as well as a comprehensive review of threats to IoT systems caused by compromised IoT devices.