A new intrusion detection system based on fast learning network and particle swarm optimization

A new intrusion detection system based on fast learning network and particle swarm optimization

Supervised Intrusion Detection System is a system that has the capability of learning from examples about previous attacks to detect new attacks. Using ANN based intrusion detection is promising for reducing the number of false negative or false positives because ANN has the capability of learning f...

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Bibliographic Details
Main Authors: Ali, Mohammed Hasan, Mohamad Fadli, Zolkipli, Al Mohammed, B.A.D., Alyani, Ismail
Format: Article
Language:English
Published: IEEE 2018
Subjects:
QA75 Electronic computers. Computer science
T Technology (General)
Online Access:http://umpir.ump.edu.my/id/eprint/22096/
http://umpir.ump.edu.my/id/eprint/22096/
http://umpir.ump.edu.my/id/eprint/22096/
http://umpir.ump.edu.my/id/eprint/22096/1/08326489.pdf
id ump-22096
recordtype eprints
spelling ump-220962018-09-24T06:14:16Z http://umpir.ump.edu.my/id/eprint/22096/ A new intrusion detection system based on fast learning network and particle swarm optimization Ali, Mohammed Hasan Mohamad Fadli, Zolkipli Al Mohammed, B.A.D. Alyani, Ismail QA75 Electronic computers. Computer science T Technology (General) Supervised Intrusion Detection System is a system that has the capability of learning from examples about previous attacks to detect new attacks. Using ANN based intrusion detection is promising for reducing the number of false negative or false positives because ANN has the capability of learning from actual examples. In this article, a developed learning model for Fast Learning Network (FLN) based on particle swarm optimization(PSO) has been proposed and named as PSO-FLN. The model has been applied to the problem of intrusion detection and validated based on the famous dataset KDD99. Our developed model has been compared against a wide range of meta-heuristic algorithms for training ELM, and FLN classifier. PSO-FLN has outperformed other learning approaches in the testing accuracy of the learning. IEEE 2018-03-27 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/22096/1/08326489.pdf Ali, Mohammed Hasan and Mohamad Fadli, Zolkipli and Al Mohammed, B.A.D. and Alyani, Ismail (2018) A new intrusion detection system based on fast learning network and particle swarm optimization. IEEE Access, 6. 20255 -20261. ISSN 2169-3536 https://ieeexplore.ieee.org/document/8326489/ 10.1109/ACCESS.2018.2820092
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic QA75 Electronic computers. Computer science
T Technology (General)
spellingShingle QA75 Electronic computers. Computer science
T Technology (General)
Ali, Mohammed Hasan
Mohamad Fadli, Zolkipli
Al Mohammed, B.A.D.
Alyani, Ismail
A new intrusion detection system based on fast learning network and particle swarm optimization
description Supervised Intrusion Detection System is a system that has the capability of learning from examples about previous attacks to detect new attacks. Using ANN based intrusion detection is promising for reducing the number of false negative or false positives because ANN has the capability of learning from actual examples. In this article, a developed learning model for Fast Learning Network (FLN) based on particle swarm optimization(PSO) has been proposed and named as PSO-FLN. The model has been applied to the problem of intrusion detection and validated based on the famous dataset KDD99. Our developed model has been compared against a wide range of meta-heuristic algorithms for training ELM, and FLN classifier. PSO-FLN has outperformed other learning approaches in the testing accuracy of the learning.
format Article
author Ali, Mohammed Hasan
Mohamad Fadli, Zolkipli
Al Mohammed, B.A.D.
Alyani, Ismail
author_facet Ali, Mohammed Hasan
Mohamad Fadli, Zolkipli
Al Mohammed, B.A.D.
Alyani, Ismail
author_sort Ali, Mohammed Hasan
title A new intrusion detection system based on fast learning network and particle swarm optimization
title_short A new intrusion detection system based on fast learning network and particle swarm optimization
title_full A new intrusion detection system based on fast learning network and particle swarm optimization
title_fullStr A new intrusion detection system based on fast learning network and particle swarm optimization
title_full_unstemmed A new intrusion detection system based on fast learning network and particle swarm optimization
title_sort new intrusion detection system based on fast learning network and particle swarm optimization
publisher IEEE
publishDate 2018
url http://umpir.ump.edu.my/id/eprint/22096/
http://umpir.ump.edu.my/id/eprint/22096/
http://umpir.ump.edu.my/id/eprint/22096/
http://umpir.ump.edu.my/id/eprint/22096/1/08326489.pdf
first_indexed 2023-09-18T22:32:42Z
last_indexed 2023-09-18T22:32:42Z
_version_ 1777416392332541952

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