A neural network for counter-terrorism

S. J. Dixon; M. B. Dixon; J. Elliott; E. Guest; D. J. Mullier

doi:10.1007/978-1-4471-2318-7_18

A neural network for counter-terrorism

S. J. Dixon, M. B. Dixon, J. Elliott, E. Guest, D. J. Mullier

School of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

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.

Original language	English
Title of host publication	Res. and Dev. in Intelligent Syst. XXVIII
Subtitle of host publication	Incorporating Applications and Innovations in Intel. Sys. XIX - AI 2011, 31st SGAI Int. Conf. on Innovative Techniques and Applications of Artificial Intel.
Publisher	Springer-Verlag
Pages	229-234
Number of pages	6
ISBN (Print)	9781447123170
DOIs	https://doi.org/10.1007/978-1-4471-2318-7_18
Publication status	Published - 2011
Event	1st SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, AI 2011 - Cambridge, United Kingdom Duration: 13 Dec 2011 → 15 Dec 2011

Conference

Conference	1st SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, AI 2011
Country/Territory	United Kingdom
City	Cambridge
Period	13/12/11 → 15/12/11

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/978-1-4471-2318-7_18

Cite this

Dixon, S. J., Dixon, M. B., Elliott, J., Guest, E., & Mullier, D. J. (2011). A neural network for counter-terrorism. In Res. and Dev. in Intelligent Syst. XXVIII: Incorporating Applications and Innovations in Intel. Sys. XIX - AI 2011, 31st SGAI Int. Conf. on Innovative Techniques and Applications of Artificial Intel. (pp. 229-234). Springer-Verlag. https://doi.org/10.1007/978-1-4471-2318-7_18

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title = "A neural network for counter-terrorism",

abstract = "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.",

author = "Dixon, {S. J.} and Dixon, {M. B.} and J. Elliott and E. Guest and Mullier, {D. J.}",

year = "2011",

doi = "10.1007/978-1-4471-2318-7_18",

language = "English",

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pages = "229--234",

booktitle = "Res. and Dev. in Intelligent Syst. XXVIII",

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note = "1st SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, AI 2011 ; Conference date: 13-12-2011 Through 15-12-2011",

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Dixon, SJ, Dixon, MB, Elliott, J, Guest, E & Mullier, DJ 2011, A neural network for counter-terrorism. in Res. and Dev. in Intelligent Syst. XXVIII: Incorporating Applications and Innovations in Intel. Sys. XIX - AI 2011, 31st SGAI Int. Conf. on Innovative Techniques and Applications of Artificial Intel.. Springer-Verlag, pp. 229-234, 1st SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, AI 2011, Cambridge, United Kingdom, 13/12/11. https://doi.org/10.1007/978-1-4471-2318-7_18

A neural network for counter-terrorism. / Dixon, S. J.; Dixon, M. B.; Elliott, J. et al.
Res. and Dev. in Intelligent Syst. XXVIII: Incorporating Applications and Innovations in Intel. Sys. XIX - AI 2011, 31st SGAI Int. Conf. on Innovative Techniques and Applications of Artificial Intel.. Springer-Verlag, 2011. p. 229-234.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Elliott, J.

AU - Guest, E.

AU - Mullier, D. J.

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Y1 - 2011

N2 - 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.

AB - 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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AN - SCOPUS:84881516645

SN - 9781447123170

SP - 229

EP - 234

BT - Res. and Dev. in Intelligent Syst. XXVIII

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T2 - 1st SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, AI 2011

Y2 - 13 December 2011 through 15 December 2011

ER -

A neural network for counter-terrorism

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