Title :
A novel intrusion detection system based on the 2-dimensional space distribution of average matching degree
Author :
Wang, Tuo ; Mabu, Shingo ; Lu, Nannan ; Hirasawa, Kotaro
Author_Institution :
Grad. Sch. of Inf., Production & Syst., Waseda Univ., Kitakyushu, Japan
Abstract :
Because of the increasing reliance on the Internet and its worldwide connectivity, Intrusion Detection System (IDS) has attracted the attention of many researchers to strengthen the Internet security. In the field of IDS, anomaly detection still is not a mature technology yet compared with misuse detection. In this paper, a classification model (called Distance-based Classification Model) is improved, which considers both misuse detection and anomaly detection. The evaluation of the proposed model is carried out over NSL-KDD data sets, which consists of selected records of the complete KDD data sets.
Keywords :
Internet; pattern classification; security of data; 2-dimensional space distribution; Internet security; NSL-KDD data sets; anomaly detection; average matching degree; distance-based classification model; intrusion detection system; misuse detection; Association rules; Data models; Economic indicators; Intrusion detection; Manganese; Training; Training data; Distance-based Classification Model; Intrusion Detection System; KSL-KDD data sets; NSL-KDD data sets;
Conference_Titel :
SICE Annual Conference (SICE), 2011 Proceedings of
Conference_Location :
Tokyo
Print_ISBN :
978-1-4577-0714-8
