The intrusion or attack in the computer network is one of the most important issues in Cloud
environment. Due to enormous network traffic, dynamic and incremental learning is …

Proposed a method of detecting intrusion using incremental SVM based on key feature
selection. A center SVM summarizes the distributed samples and incorporates them to build …

Network attacks have become more pervasive in the cyber world. There are various attacks
such as denial of service, scanning, privilege escalation that is increasing day by day …

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 …

In the world today, the security of the computer system is of great importance, And in the last
few years, there have seen an affected growth in the amount of intrusions that intrusion …

In this paper we propose a new classifier called an incremental learning algorithm based on
support vector machine with Mahalanobis distance (ISVMM). Prediction of the incoming data …

One of the most crucial tool for network defense is an Intrusion Detection Systems (IDS).
Several supervised machine learning algorithms exist that deal with high volumes of training …

Intrusion detection occupies a decision position in solving the network security problems.
Support Vector Machines (SVMs) are one of the widely used intrusion detection techniques …

For the network data sets too large, too slow learning speed problem, in this paper, a SVM
algorithm based on space block and sample density is proposed and applied into intrusion …

This paper considers the feature selection problem for data classification in the absence of
data labels. It first proposes an unsupervised feature selection algorithm, which is an …