While the use of the Internet of things technology brings people convenience in life, it also brings many security problems. Therefore, a complete and robust system should be established to protect the security of the Internet of things, so that the objects of the Internet of things can communicate safely and effectively. The detection system has become a key technology to protect the security of the Internet of things. With the continuous development of machine learning and deep learning, researchers have designed a large number of effective intrusion detection systems. This paper reviews these studies. Firstly, the differences between the current Internet of things security and traditional system security are compared. Secondly, the intrusion detection system is classified in detail from the detection technology, data source, architecture and working methods. Thirdly, starting from the data set, the current stage of the Internet of things intrusion detection system based on machine learning is explained. Finally, the future development direction is discussed.