Abstract
Research on data anomaly intrusion detection in the Internet of Things (IoT) environment is still insufficient, and there are still many practical problems that need to be solved urgently. At present, the deep integration of Artificial Intelligence (AI) technology and IoT, and intelligent technologies such as machine learning have gradually been applied to the field of intrusion detection of the Internet of Things. Therefore, this paper conducts the latest and in-depth research on the efficient and accurate intrusion detection technology used in computers, analyzes the security threats facing the Internet of Things, and summarizes the latest technology and evaluation indicators of intrusion detection. This paper can promote the improvement of large-scale industrial network security detection performance under the new situation to a certain extent and has important theoretical significance and practical application value for ensuring the rapid and healthy development of today's industrial IoT security environment.
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CITATION STYLE
Long, J., Fang, F., & Luo, H. (2021). A Survey of Machine Learning-based IoT Intrusion Detection Techniques. In Proceedings - 2021 IEEE 6th International Conference on Smart Cloud, SmartCloud 2021 (pp. 7–12). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/SmartCloud52277.2021.00009
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