Applying Neural Network to U2R Attacks

Iftikhar , Ahmad and Azween, Abdullah and Abdullah , S. Alghamdi (2010) Applying Neural Network to U2R Attacks. In: 2010 IEEE Symposium on Industrial Electronics and Applications (ISIEA 2010) , 3-6/10, Penang, Malaysia.

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Intrusion detection using artificial neural networks is an ongoing area and thus interest in this field has increased among the researchers. Therefore, in this paper we present a system for tackling User to Root (U2R) attacks using generalized feedforward neural network. A backpropagation algorithm is used for training and testing purpose. The system uses sampled data from Kddcup99 dataset, an attack database that is a standard for evaluating the security detection mechanisms. The system is implemented in two phases such as training phase and testing phase. The developed system is applied to different U2R attacks to test its performance. Furthermore, the results indicate that this approach is more precise and accurate in case of false positive, false negative and detection rate.

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:3081
Deposited By: Assoc Prof Dr Azween Abdullah
Deposited On:12 Nov 2010 01:19
Last Modified:12 Nov 2010 01:19

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