Remote to Local Attack Detection Using Supervised Neural Network

Iftikhar, Ahmad and Azween, Abdullah and Abdullah , S. Alghamdi (2010) Remote to Local Attack Detection Using Supervised Neural Network. In: The 5th International Conference for Internet Technology and Secured Transactions, 8-11/11, London, UK.

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In order to determine Remote to Local (R2L) attack, an intrusion detection technique based on artificial neural network is presented. This technique uses sampled dataset from Kddcup99 that is standard for benchmarking of attack detection tools. The backpropagation algorithm is used for training the feedforward neural network. The developed system is applied to R2L attacks. Moreover, experiment indicates this technique has comparatively low false positive rate and false negative rate, consequently it effectively resolves the deficiency of existing intrusion detection approaches

Item Type:Conference or Workshop Item (Paper)
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments / MOR / COE:Research Institutes > Megacities
ID Code:3083
Deposited By: Assoc Prof Dr Azween Abdullah
Deposited On:12 Nov 2010 01:19
Last Modified:31 Dec 2012 04:06

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