DocumentCode
3589702
Title
Network intrusion detection based on heterogeneous distance
Author
Du Hongle
Author_Institution
Sch. of Math. & Comput. Applic., Shangluo Univ., Shangluo, China
fYear
2014
Firstpage
1
Lastpage
5
Abstract
Separation measure plays a decisive role in the multi-class support vector machine. Combine with Heterogeneity of network connection data, this paper propose improved HTSVM based on heterogeneous distance. Firstly, define the heterogeneous distance; then compute the separation measure according to the heterogeneous distance between each two classes; then compute the sample that should belong to class according to separation measure. Finely, this method is applied to the network intrusion detection. And simulate with KDDCUP1999 dataset. Experiment result show the method can accurately measure the similarity between heterogeneous data and improve the accurate rate of classification accuracy.
Keywords
computer network security; learning (artificial intelligence); statistical analysis; support vector machines; HTSVM; KDDCUP1999 dataset; heterogeneous data; heterogeneous distance; machine learning; multiclass support vector machine; network connection data heterogeneity; network intrusion detection; separation measure; statistical learning theory; Heterogeneous Distance; Intrusion Detection; Separation Measure; Support Vector Machine;
fLanguage
English
Publisher
iet
Conference_Titel
Cyberspace Technology (CCT 2014), International Conference on
Print_ISBN
978-1-84919-928-5
Type
conf
DOI
10.1049/cp.2014.1354
Filename
7106853
Link To Document