Abstract
At this stage, the security protection system of power IOT distribution terminals lacks effective anomaly intrusion detection methods, and the distribution terminals of power IOT have the characteristics of large number and wide range, which plays an important role in maintaining the normal operation of power IOT. Once the distribution terminal encounters illegal intrusion, it can lead to the damage of the important infrastructure of the distribution terminal of the power Internet of things, and pose a great security threat to the stable operation of the power Internet of things. This paper analyzes the content of building the network flow order of distribution terminals for the power Internet of things. From the aspects of basic attribute selection, data processing, building the network flow order, attribute classification, abnormal feature extraction, and realizing abnormal monitoring, it deeply discusses the abnormal intrusion dynamic monitoring method of the network flow order for the power Internet of things, in order to accurately monitor the abnormal intrusion dynamic data and enhance the abnormal intrusion dynamic monitoring effect, Improve the level of abnormal intrusion dynamic monitoring technology, and effectively ensure the safe and stable operation of power distribution terminals of the Internet of things.
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