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Investigating Supervised Neural Networks to Intrusion Detection

Iftikhar , Ahmad and Azween, Abdullah and Abdullah , S. Alghamdi (2010) Investigating Supervised Neural Networks to Intrusion Detection. ICIC Express Letters, 4 (6). pp. 1-6. ISSN 1881-803X

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Abstract

The application of neural networks towards intrusion detection is becoming a mainstream and a useful approach to deal with several current issues in this area. Currently, security in computer and network is a main problem because a single intrusion may cause a very big harm. A variety of neural networks is applied to intrusion detection approaches during last few years and still is being used in this area .In this paper; we investigated different supervised neural networks (SNN) to intrusion detection. This work describes an analysis of different supervised neural network applied to intrusion detection mechanisms using Multi-criteria analysis (MCA) technique. Further, conclusion on results is made and direction for future works is presented. The outcome of this effort may assist and direct the security implementers in the area of intrusion detection systems or approaches.

Item Type:Article
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments / MOR / COE:Research Institutes > Megacities
ID Code:3084
Deposited By: Assoc Prof Dr Azween Abdullah
Deposited On:12 Nov 2010 01:30
Last Modified:31 Dec 2012 04:06

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