Self-adaptive updating network intrusion detection method
A network intrusion detection and adaptive update technology, applied in the field of cyberspace security, can solve problems such as being unable to adapt to changes in the environment, not having automatic update learning, and unable to automatically trigger automatic update of intrusion detection models.
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[0071] combine figure 1 As shown, an adaptive update network intrusion detection method, including:
[0072] Step S100: training multiple classification models in different feature spaces through feature space mapping;
[0073] Step S200: Multiple classification models cooperate to perform intrusion detection;
[0074] Step S300: multiple classification models are automatically updated and triggered according to the difference between the current sample distribution and the historical sample distribution;
[0075] Step S400: Multiple classification models cooperate to perform adaptive update.
[0076] Periodically calculate the relative entropy changes between the newly collected sample distribution and the historical sample distribution, and automatically determine the timing of triggering the update of the intrusion detection model; 2) Through the collaborative learning of multi-classification models, the adaptive update of the intrusion detection model is realized.
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