Authors: Qinghua Zhang; Yuzhen Fu
Addresses: College of Electronic Information and Computer, Maoming University, 525000 Maoming Guangdong, China. ' Department of Computer Engineering, Maoming Vocational and Technical College, 525000 Maoming Guangdong, China
Abstract: In the last years, a lot of effort has been put into solving the intrusion detection problem. In this paper, we present an experimental framework for a Network Intrusion Detection System (NIDS) based on the immunological approach. In the data collection stage, we use the adaptive sampling algorithm, according to the dynamic characters of detection data, and intrude the sliding window into the model. Comparing with this model, data-processing capabilities and the fault tolerance of model have further improved. Expand the application of data streaming mining technologies.
Keywords: self-adaptive; adaptive sampling; sliding window; network intrusion detection; network security; modelling; fault tolerance; data streaming; data mining; adaptive immune systems; artificial immune systems.
International Journal of Systems, Control and Communications, 2011 Vol.3 No.3, pp.280 - 286
Published online: 11 Sep 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article