Weighted naive Bayes intrusion detection method and device based on particle swarm optimization

The invention discloses a weighted naive Bayes intrusion detection method and device based on particle swarm optimization, and belongs to the technical field of computer network security, and the method comprises the following steps: collecting original data for intrusion detection; preprocessing the original data; feature extraction is carried out on the preprocessed original data, feature attributes are subjected to coarse removal and fine removal, and a needed data set is obtained; optimizing the weight of the weighted naive Bayes by adopting a particle swarm optimization algorithm, and constructing a weighted naive Bayes classifier; training a weighted naive Bayesian classifier by using the data set to obtain an optimized weighted naive Bayesian classifier; and performing intrusion detection by using the optimized weighted naive Bayes classifier, and storing a detection result. According to the method, the advantages of the particle swarm algorithm and the weighted naive Bayes algorithm are combined, and