Machine Learning based IoT Security: A Systematic Review

IoT is growing very fast and is used in different sectors like healthcare, transportation, education, agriculture, and smart homes by connecting different devices through net-works. IoT uses internet connectivity than traditional devices like desktops and laptops. Due to this growth, IoT faced security challenges such as unauthorized access and other malware at-tacks. Machine Learning techniques are used to detect anomalies, identify unusual behaviors, and prevent attacks. Our research focuses on how Machine learning can be used to prevent attacks and protect IoT devices, ensuring that they are fully secured. Furthermore, our study shows the common vulnerabilities that happen in IoT devices, and how to overcome them using Machine Learning.