The Internet of Things (IoT) integrates billions of smart devices that can communicate with one another with minimal human intervention. It is one of the fastest developing fields in the history of computing. It is a promising system that needs new protocols and architectures in comparison to conventional networks. Security has to be tackled effectively in this system as it considered one of the main critical issues. Because heterogeneity is an inherent feature of IoT, it raises a large number of security concerns that must be addressed through new methodologies like cryptographic algorithms to mitigate the risk. The goal of this work is to provide a comprehensive survey of ML methods and recent advances and methods that can be used to develop enhanced security methods for IoT systems. IoT security threats that are related to inherent or newly introduced threats are presented, and various potential IoT system attack surfaces and the possible threats related are discussed.