Handling concept drifts in incremental learning with support vector machines
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Anomaly Detection over Noisy Data using Learned Probability Distributions
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Modeling intrusion detection system using hybrid intelligent systems
Journal of Network and Computer Applications - Special issue: Network and information security: A computational intelligence approach
Adaptive real-time anomaly detection with incremental clustering
Information Security Tech. Report
Network anomaly detection with incomplete audit data
Computer Networks: The International Journal of Computer and Telecommunications Networking
Using Density-Based Incremental Clustering for Anomaly Detection
CSSE '08 Proceedings of the 2008 International Conference on Computer Science and Software Engineering - Volume 03
Network intrusion detection system using genetic network programming with support vector machine
Proceedings of the International Conference on Advances in Computing, Communications and Informatics
Hi-index | 12.05 |
We develop an improved incremental SVM algorithm, named RS-ISVM, to deal with network intrusion detection. To reduce the noise generated by feature differences, we propose a modified kernel function U-RBF, with the mean and mean square difference values of feature attributes embedded in kernel function RBF. Then, given the oscillation problem that usually occurs in traditional incremental SVM's follow-up learning process, we present a reserved set strategy which can keep those samples that are more likely to be the support vectors in the following computation process. Moreover, in order to shorten the training time, a concentric circle method is suggested to be used in selecting samples to form the reserved set. Academic researches and data experiments show that RS-ISVM can ease the oscillation phenomenon in the learning process and achieve pretty good performance, meanwhile, its reliability is relative high.