Network Intrusion Detection Using Neural Network Techniques

Abstract

AbstractA network intrusion (NIDS) detection system is an essential element of Internet security. It plays a major role in detecting malicious attacks and preventing network intrusion. Intrusion detection model can be obtained by training intrusion samples with various machine learning algorithms such as k-means, support vector machine, naïve Bayes classifier and decision tree. The traditional machine learning model has to select the features on its own and has some drawbacks such as low detection rate. In this regard, a model using convolutional neural networks is proposed. In this model, functional features are extracted from input samples and the samples are classified accurately based on those functional features.KeywordsIntrusion detectionDimensionality reductionConvolution neural network (CNN)Intrusion detection systemNetwork security