Intrusion Detection Based on SVM and Cross-correlation of Sample Sequences
Mingxing He · Journal of the China Railway Society · 2007
The intrusion detection using system call sequences has been widely studied.This kind of intrusion detection is usually based on the artificial intelligence,such as SVM(the support vector machine),HMM(the hidden markov model) and NN(the neural network).For this kind of intelligent intrusion detection system,the training dataset is important to the performance of the IDS.Applying cross-correlation to select the training data set can greatly improve the performance of the intrusion detection system.Cross-correlation is defined as a kind of important properties among system call sequences.In this paper,a new method based on the cross-correlation sample and SVM is proposed.This method is evaluated by the system call data set from Prof.Forrest.The simulation results show that this method has better intrusion detection rates.