Detection method of network intrusion based on learning Petri nets

A method of intrusion detection based on neural network (NN) has flaws of slower learning speed, hardness in converging and deficiency of classifier capability. The learning Petri nets (LPN) were adopted to construct the method of network intrusion detection. LPN is superior to NN in the realization of nonlinear and discontinuous functions. The test result indicates that the classifier based on LPN has better recognizing precision and faster learning speed compared with the classifier based on the same structure NN.