Applying neural network to U2R attacks

@article{Ahmad2010ApplyingNN,
  title={Applying neural network to U2R attacks},
  author={Iftikhar Ahmad and Azween Bin Abdullah and Abdullah Sharaf Alghamdi},
  journal={2010 IEEE Symposium on Industrial Electronics and Applications (ISIEA)},
  year={2010},
  pages={295-299}
}
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… CONTINUE READING
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Showing 1-10 of 18 references

Evaluating Intrusion Detection Approaches Using Multi-criteria Decision Making Technique, Information Sciences and Computer Engineering

  • Iftikhar Ahmad, Azween B. Abdullah, Abdullah S. Alghamdi
  • IJISCE), Australia,
  • 2010
1 Excerpt

A.Kannan, “An inrusion detection System Based on Multiple Level Hybrid Classifier using Enhanced C045

  • L.Prema Rajeswari
  • IEEE-INTERNATIONAL CONFERENCE on Signal…
  • 2008
1 Excerpt

Fundamentals of Neural Networks Architecture, Algorithm, and Applications, Pearson Education, Inc

  • Laurene Fausett
  • 2008
1 Excerpt

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