Intrusion Detection using Deep Belief Network
Kamran Raza, Syed Hasan Adil · DOAJ (DOAJ: Directory of Open Access Journals) · 2014
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