A Neural Network for Counter-Terrorism

نویسندگان

  • Sam J. Dixon
  • Mark B. Dixon
  • John Elliott
  • Elizabeth Guest
  • Duncan J. Mullier
چکیده

This article presents findings concerned with the use of neural networks in the identification of deceptive behaviour. A game designed by psychologists and criminologists was used for the generation of data used to test the appropriateness of different AI techniques in the quest for counter-terrorism. A feed forward back propagation network was developed and subsequent neural network experiments showed on average a 60% success rate and at best a 68% success rate for correctly identifying deceptive behaviour. These figures indicate that, as part of an investigator support system, a neural network would be a valuable tool in the identification of terrorists prior to an attack.

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تاریخ انتشار 2011