Intelligent unmanned equipment group network anomaly detection method and system based on machine learning
An anomaly detection and machine learning technology, which is applied in the field of abnormal detection of intelligent unmanned equipment networking, can solve problems such as poor detection effect of intelligent unmanned equipment networking anomalies, difficulty in abnormal detection of driving data and network data, etc.
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[0035] The present invention will be described in further detail below in conjunction with the accompanying drawings.
[0036] A machine-learning-based intelligent unmanned equipment networking anomaly detection method proposed by the present invention mainly consists of two stages: the machine learning stage and the anomaly detection stage, see figure 1 process shown.
[0037]First, the driving data and network data in the intelligent unmanned equipment network are extracted, and the PCA algorithm is used to reduce the dimensionality of all the extracted feature vectors, and then the DBSCAN algorithm is used to perform density clustering on the reduced features, which are divided into normal events and exceptions. Then input the feature vector of the divided event into the CNN algorithm for feature extraction, and then input it into the SVM algorithm to realize the binary classification, so that the abnormal detection of the intelligent unmanned device network can be realize...
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