Protecting the security of these systems is becoming more and more important as the deployment of Internet of Things (IoT) devices keeps growing. IoT networks depends mainly on sensor nodes, which are very sensitive to security threats. Therefore, early detection of attacks is extremely important for protecting the security of the system and minimizing more serious breaches. These sensors run the risk of malfunctioning devices, compromising the system, and data breaches in the absence of efficient detection measures. To improve IoT security through better early detection mechanisms, this research evaluates current methods for attack detection within IoT node sensors. This research does a thorough literature analysis from recently released papers and looks at several security techniques, particularly those that use machine learning techniques to detect attacks. Important findings highlight common practices, major holes and difficulties in the field. The report’s strength is in its helpful recommendations on how to improve IoT security using strong early threat detection methods. The objective of this research is to ensure the reliability and safety of IoT networks by filling up the holes that have been found and putting up a framework, which would improve the general strength and efficiency of the system.