Security in Iot: Systematic Review
Koti Tejasvi, Ruqqaiya Begum, M. A. Jabbar · Apple Academic Press eBooks · 2024
IoT platforms have grown into a worldwide powerhouse over the past ten years that dominates boosting human existence with its uncontrolled smart services throughout every aspect of our daily lives. The ease of accessibility and the rapidly growing need for smart devices and networks are causing IoT to face more security challenges than ever before. By using already-existing security measures, IoT may be safeguarded. The explosions in technology as well as the different attack patterns and their severity make traditional methods less effective. Therefore, the next-generation IoT system needs a robust, constantly improved, and current security system. A considerable technical advancement in machine learning (ML) has created a number of new research opportunities for tackling existing and upcoming IoT challenges. To do this, ML is being utilized as a strong tool to spot assaults and strange behaviors in networks and smart devices. The architecture of IoT is explored in this book chapter after a thorough literature ML methods research that emphasizes the need of IoT security in light of a variety of possible attacks and potential IoT security solutions based on ML.