Cover Image

Application of Artificial Neural Network in Detection of Probing Attacks

The prevention of any type of cyber attack is indispensable because a single attack may break the security of computer and network systems. The hindrance of such attacks is entirely dependent on their detection. The detection is a major part of any security tool such as Intrusion Detection System (I...

Full description

Saved in:
Bibliographic Details
Main Authors: Ahmad, iftikhar, Azween, Abdullah, Alghamdi, Abdullah
Format: Conference or Workshop Item
Published: 2009
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.utp.edu.my/2590/1/IEEE-ahmad-eprinted.pdf
http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=5356382&isnumber=5356300
http://eprints.utp.edu.my/2590/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utp.eprints.2590
record_format eprints
spelling my.utp.eprints.25902017-01-19T08:25:12Z Application of Artificial Neural Network in Detection of Probing Attacks Ahmad, iftikhar Azween, Abdullah Alghamdi, Abdullah QA75 Electronic computers. Computer science The prevention of any type of cyber attack is indispensable because a single attack may break the security of computer and network systems. The hindrance of such attacks is entirely dependent on their detection. The detection is a major part of any security tool such as Intrusion Detection System (IDS), Intrusion Prevention System (IPS), Adaptive Security Alliance (ASA), check points and firewalls. Consequently, in this paper, we are contemplating the feasibility of an approach to probing attacks that are the basis of others attacks in computer network systems. Our approach adopts a supervised neural network phenomenon that is majorly used for detecting security attacks. The proposed system takes into account Multiple Layered Perceptron (MLP) architecture and resilient backpropagation for its training and testing. The system uses sampled data from Kddcup99 dataset, an attack database that is a standard for evaluating the security detection mechanisms. The developed system is applied to different probing attacks. Furthermore, its performance is compared to other neural networks’ approaches and the results indicate that our approach is more precise and accurate in case of false positive, false negative and detection rate. 2009-10-06 Conference or Workshop Item PeerReviewed application/pdf http://eprints.utp.edu.my/2590/1/IEEE-ahmad-eprinted.pdf http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=5356382&isnumber=5356300 Ahmad, iftikhar and Azween, Abdullah and Alghamdi, Abdullah (2009) Application of Artificial Neural Network in Detection of Probing Attacks. In: 2009 IEEE Symposium on Industrial Electronics and Applications (ISIEA 2009), 4-6 October, 2009, Kuala Lumpur . http://eprints.utp.edu.my/2590/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Ahmad, iftikhar
Azween, Abdullah
Alghamdi, Abdullah
Application of Artificial Neural Network in Detection of Probing Attacks
description The prevention of any type of cyber attack is indispensable because a single attack may break the security of computer and network systems. The hindrance of such attacks is entirely dependent on their detection. The detection is a major part of any security tool such as Intrusion Detection System (IDS), Intrusion Prevention System (IPS), Adaptive Security Alliance (ASA), check points and firewalls. Consequently, in this paper, we are contemplating the feasibility of an approach to probing attacks that are the basis of others attacks in computer network systems. Our approach adopts a supervised neural network phenomenon that is majorly used for detecting security attacks. The proposed system takes into account Multiple Layered Perceptron (MLP) architecture and resilient backpropagation for its training and testing. The system uses sampled data from Kddcup99 dataset, an attack database that is a standard for evaluating the security detection mechanisms. The developed system is applied to different probing attacks. Furthermore, its performance is compared to other neural networks’ approaches and the results indicate that our approach is more precise and accurate in case of false positive, false negative and detection rate.
format Conference or Workshop Item
author Ahmad, iftikhar
Azween, Abdullah
Alghamdi, Abdullah
author_facet Ahmad, iftikhar
Azween, Abdullah
Alghamdi, Abdullah
author_sort Ahmad, iftikhar
title Application of Artificial Neural Network in Detection of Probing Attacks
title_short Application of Artificial Neural Network in Detection of Probing Attacks
title_full Application of Artificial Neural Network in Detection of Probing Attacks
title_fullStr Application of Artificial Neural Network in Detection of Probing Attacks
title_full_unstemmed Application of Artificial Neural Network in Detection of Probing Attacks
title_sort application of artificial neural network in detection of probing attacks
publishDate 2009
url http://eprints.utp.edu.my/2590/1/IEEE-ahmad-eprinted.pdf
http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=5356382&isnumber=5356300
http://eprints.utp.edu.my/2590/
_version_ 1738655203679272960
score 13.211869

Similar Items