High Impact Factor : 4.396 icon | Submit Manuscript Online icon |

Intrusion Detection System on KDDCUPS’99 Dataset with SVM & KNN

Author(s):

Preeti Yadav , Guru Kashi University; Jaspreet Kaur, guru kashi university

Keywords:

Intrusion, SVM, PCNN, KDDCups’99 etc

Abstract

Intrusion Detection System (IDS) becomes a crucial a part of each laptop or network system. Intrusion detection (ID) may be a mechanism that has security for each computers and networks. Feature choice and have reduction is very important space of analysis in intrusion direction system. the dimensions and attribute of intrusion file ar terribly massive. within the analysis work intrusion detection totally different issues ar two-faced. A hybrid model for feature choice and intrusion detection is very important issue in intrusion detection. the choice of feature in attack attribute and traditional traffic attribute is difficult task. Experimental results performed on KDDCup’99 data set and real network data indicate. The Intrusion from network from different dataset using KNN, SVM and KNN in Matlab tool. A comparative analysis of different feature selection methods based on KDDCUP’99 benchmark dataset is applied. The performance is evaluated in terms of regression, slop and Accuracy of the testing dataset.

Other Details

Paper ID: IJSRDV4I50102
Published in: Volume : 4, Issue : 5
Publication Date: 01/08/2016
Page(s): 64-68

Article Preview

Download Article