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Intrusion Detection with Probabilistic Neural Network: Comparative Analysis

EasyChair Preprint no. 129

4 pagesDate: May 15, 2018

Abstract

The use of machine learning techniques has significantly increased recently. The classification of normal or abnormal situations in network traffic is successfully applied with machine learning techniques. It is possible to encounter False Positive situations during the classification process. With Probabilistic Neural Network (PNN) model, it is aimed to explore the intrusion and its types within network traffic with probabilistic distribution. Knowledge Discovery Dataset (KDD99) will be used in this study.

Keyphrases: Intrusion Detection, KDD99, Probabilistic Neural Network

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:129,
  author = {Ibrahim Atay},
  title = {Intrusion Detection with Probabilistic Neural Network: Comparative Analysis},
  howpublished = {EasyChair Preprint no. 129},

  year = {EasyChair, 2018}}
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