Intrusion Recognition Using Neural Networks

Author

Golovko, Vladimir ; Kochurko, Pavel

Author_Institution

Brest State Tech. Univ., Brest

fYear

2005

fDate

5-7 Sept. 2005

Firstpage

108

Lastpage

111

Abstract

Intrusion detection techniques are of great importance for computer network protecting because of increasing the number of remote attack using TCP/IP protocols. There exist a number of intrusion detection systems, which are based on different approaches for anomalous behavior detection. This paper focuses on applying neural networks for attack recognition. It is based on multilayer perceptron. The 1999 KDD Cup data set is used for training and testing neural networks. The results of experiments are discussed in the paper.

Keywords

computer networks; neural nets; security of data; transport protocols; TCP/IP protocols; intrusion detection systems; intrusion recognition; multilayer perceptron; neural networks; remote attack; Artificial neural networks; Computer crime; Computer networks; Intrusion detection; Multilayer perceptrons; Neural networks; Protection; Protocols; TCPIP; Telecommunication traffic; Neural networks; attack recognition; intrusion detection systems; network attacks;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2005. IDAACS 2005. IEEE

Conference_Location

Sofia

Print_ISBN

0-7803-9445-3

Electronic_ISBN

0-7803-9446-1

Type

conf

DOI

10.1109/IDAACS.2005.282950

Filename

4062101

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3236739