Detail publikace

Convergence Optimization of Backpropagation Artificial Neural Network Used for Dichotomous Classification of Intrusion Detection Dataset

HOMOLIAK, I. BREITENBACHER, D. HANÁČEK, P.

Originální název

Convergence Optimization of Backpropagation Artificial Neural Network Used for Dichotomous Classification of Intrusion Detection Dataset

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

There are distinguished two categories of intrusion detection approaches utilizing machine learning according to type of input data. The first one represents network intrusion detection techniques which consider only data captured in network traffic. The second one represents general intrusion detection techniques which intake all possible data sources including host-based features as well as network-based ones. The paper demonstrates various convergence optimization experiments of a backpropagation artificial neural network using well know NSL-KDD 1999 dataset, and thus, representing the general intrusion detection. Experiments evaluating usefulness of stratified sampling on input dataset and simulated annealing employed into the backpropagation learning algorithm are performed. Both techniques provide improvement of backpropagation's learning convergence as well as classification accuracy. After 50 training cycles, classification accuracy of 84.20% is achieved when utilizing stratified sampling and accuracy of 86.5% when both stratified sampling and simulated annealing are used. In contrast, the backpropagation by itself reaches only 76.63% accuracy. Comparing to state-of-the-art work introducing the NSL-KDD dataset, there is achieved accuracy higher about 4.5%.

Klíčová slova

artificial neural network, backpropagation, data mining, intrusion detection

Autoři

HOMOLIAK, I.; BREITENBACHER, D.; HANÁČEK, P.

Vydáno

1. 3. 2017

ISSN

1796-203X

Periodikum

Journal of Computers

Ročník

12

Číslo

2

Stát

Čínská lidová republika

Strany od

143

Strany do

155

Strany počet

13

URL

http://www.jcomputers.us/vol12/jcp1202-06.pdf

BibTex

@article{BUT133490,
  author="Ivan {Homoliak} and Dominik {Breitenbacher} and Petr {Hanáček}",
  title="Convergence Optimization of Backpropagation Artificial Neural Network Used for Dichotomous Classification of Intrusion Detection Dataset",
  journal="Journal of Computers",
  year="2017",
  volume="12",
  number="2",
  pages="143--155",
  doi="10.17706/jcp.12.2.143-155",
  issn="1796-203X",
  url="http://www.jcomputers.us/vol12/jcp1202-06.pdf"
}