Network intrusion detection method based on space-time feature fusion
A technology for network intrusion detection and spatio-temporal features, applied in data exchange networks, neural learning methods, biological neural network models, etc., can solve the problems of decreased detection accuracy, high algorithm redundancy, long computing time, etc., and achieve high accuracy rate, low false positive rate and false negative rate, and the effect of excellent generalization ability
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[0023] In order to make the purpose, technical solutions, and advantages of this application clearer, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the application, and not used to limit the application.
[0024] According to the characteristics of network traffic data, detecting time domain features and spatial domain features are the two most commonly used detection methods in intrusion detection. Only one of the time and space features is used as the detection object, which is obviously not comprehensive. Therefore, the fusion detection method is adopted, and this application uses two features at the same time and combines them to classify the original network data stream.
[0025] In one embodiment, this application is a network intrusion detection method based on spatiotemporal feature fusion, such as figure 1 S...
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