Network intrusion detection method and system based on fuzzy implicit conditional random field model
A hidden conditional random field, network intrusion detection technology, applied in transmission systems, digital transmission systems, data exchange networks, etc., can solve the problem of long-distance correlation of observation sequence uncertainty, and achieve the effect of good intrusion detection effect.
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Embodiment 1
[0071] This embodiment provides a network intrusion detection method based on a fuzzy implicit conditional random field model, including the following steps:
[0072] Step 1: Use network data collection tools to collect network instances, and randomly select normal network instances and abnormal network instances as training data sets for the fuzzy latent conditional random field model;
[0073] Step 2: Preprocessing the collected network instances;
[0074] Step 3: Perform feature selection on the preprocessed network instance;
[0075] Step 4: The fuzzy implicit conditional random field model uses the selected features to train and generate a detection model;
[0076] Step 5: Use the detection model generated in step 4 to detect the network instance in actual operation;
[0077] Step 6: Perform corresponding processing on the network intrusion detection, block the network instance when it is detected as an abnormal network instance; allow the network instance to run when i...
Embodiment 2
[0111] like figure 1 Shown: the intrusion detection system based on fuzzy implicit conditional random field of the present invention includes a network instance collection module, an instance preprocessing module, a feature selection module, a detection model generation module, an instance detection module and a result processing module.
[0112] The training data set module is used to collect network instances using network data collection tools, and randomly select normal network instances and abnormal network instances as the training data sets of the fuzzy implicit conditional random field model;
[0113] The preprocessing module is used to preprocess the collected network instances;
[0114] The feature selection module is used to perform feature selection on the preprocessed network instance;
[0115] The detection model generating module is used for the fuzzy implicit conditional random field model to generate a detection model using selected feature training;
[0116] ...
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