@inproceedings{ debar_application_1992,
  address = {Baltimore, MD, USA},
  title = {An application of a recurrent network to an intrusion detection system},
  volume = {2},
  isbn = {0-7803-0559-0},
  url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=226942},
  doi = {10.1109/IJCNN.1992.226942},
  abstract = {We present an application of recurrent neural networks for intrusion detection. Such algorithms have been widely studied for time series prediction. Due to the characteristics of the temporal series that we consider, we have chosen a partially recurrent network for our application. After a description of the reactions of the network on classical problems, we present a prototype that we use to demonstrate the capability of neural nets in the field of intrusion detection.},
  booktitle = {Proceedings of the {International} {Joint} {Conference} on {Neural} {Networks} ({IJCNN} 1992)},
  publisher = {IEEE Computer Society Press},
  author = {Debar, Hervé and Dorizzi, Bernadette},
  month = {June},
  year = {1992},
  note = {00095 bibtex: debar1992application},
  keywords = {Application software, Computer hacking, Cryptography, Intrusion detection, Neural networks, Operating systems, Prototypes, Recurrent neural networks, access control, anomaly detection, computer security, recurrent neural nets, safety systems, security of data, user behavior model},
  pages = {478--483}
}

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