Details

Autor(en) / Beteiligte

• KAMRAN RAZA
• SYED HASAN ADIL

Titel

Intrusion Detection using Deep Belief Network

Ist Teil von

• Mehran University Research Journal of Engineering and Technology, 2014-10, Vol.33 (4), p.485-491

Ort / Verlag

Mehran University of Engineering and Technology

Erscheinungsjahr

2014

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• This paper proposes an intrusion detection technique based on DBN (Deep Belief Network) to classify four intrusion classes and one normal class using KDD-99 dataset. The proposed technique is based on two phases: in first phase it removes the class imbalance problem and in the next, it applies DBN followed by FFNN (Feed-Forward Neural Network) to build a prediction model. The obtained results are compared with those given in [9]. The prediction accuracy of our model shows promising results on both intrusion and normal patterns.