Abstract
Situation Awareness area deals with an ever-growing amount of data to be processed. Decision makers need new tools to swiftly assess a situation, in spite of the huge amount of information to interpret.
This reality is even truer in Crisis Analysis as military and rescue domains. Automated systems are absolutely necessary for decision makers as they enable them to save a valuable time while making decisions quickly in order to solve problems.
In this paper, we will first focus on a model of a dynamic environment designed for a military use case based on the NATO military doctrine. The scenario we have chosen is that of an army attacking the borders of a country. Intelligence services identify specific zones to observe and understand the enemy’s intentions. The model provides a topographical structure representing the different zones and the potential targets.
The second part of the following work is an automated threat propagation model which provides a heat map of the threat in case of an enemy attack. Thanks to the threat spreading representation, the system is able to propose the k-best strategies of the assailant to identify which target the enemy is likely to attack to set up an efficient and fast counter-measure.
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References
Endsley, M.R., Mica, R.: Toward a theory of situation awareness in dynamic systems. Hum. Factors 37(1), 32–64 (1995)
Niklasson, L.: Extending the scope of situation analysis. In: 2008 11th International Conference on Information Fusion, pp. 1–8. IEEE (2008)
Scott, P., Rogova, G.: Crisis management in a data fusion synthetic task environment. In: Proceedings of FUSION 2004 (2004)
Quarantelli, E.L.: Disaster crisis management: a summary of research findings. J. Manag. Stud. 25(4), 373–385 (1988)
Rivest, R.L.: Game tree searching by min/max approximation. Artif. Intell. 34(1), 77–96 (1987)
Baxter, J., Tridgell, A., Weaver, L.: Knightcap: a chess program that learns by combining td (lambda) with game-tree search. arXiv preprint cs/9901002 (1999)
Plaat, A., Schaeffer, J., Pijls, W., De Bruin, A.: Exploiting graph properties of game trees. In: AAAI/IAAI, vol. 1, pp. 234–239 (1996)
Jormakka, J., Mölsä, J.V.: Modelling information warfare as a game. J. Inf. Warfare 4(2), 12–25 (2005)
Roy, S., Ellis, C., et al.: A survey of game theory as applied to network security. In: 2010 43rd Hawaii International Conference on System Sciences, pp. 1–10. IEEE (2010)
Hamilton, et al.: Challenges in applying game theory to the domain of information warfare. In: Information Survivability Workshop (ISW) (2002)
Xiaolin, C., et al.: A Markov game theory-based risk assessment model for network information system. In: 2008 International Conference on Computer Science and Software Engineering, vol. 3, pp. 1057–1061. IEEE (2008)
Vasnier, K., et al.: Multi-level information fusion approach with dynamic bayesian networks for an active perception of the environment. In: 2018 21st International Conference on Information Fusion (FUSION) on IEEE, pp. 1844–1850 (2018)
Vasnier, K., et al.: Multi-level information fusion and active perception framework: towards a military application. In: Procedings of NATO SET-262 RSM on Artificial Intelligence for Military Multisensor Fusion Engines (2018)
Acknowledgment
The authors acknowledge that this work is partially funded by the French MoD (DGA) in the framework of CIFRE-Defense contract no 005/2016/DGA.
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Vasnier, K., Mouaddib, AI., Gatepaille, S., Brunessaux, S. (2021). Automated Threat Propagation Model Through a Topographical Environment Modelling. In: Abraham, A., Siarry, P., Ma, K., Kaklauskas, A. (eds) Intelligent Systems Design and Applications. ISDA 2019. Advances in Intelligent Systems and Computing, vol 1181. Springer, Cham. https://doi.org/10.1007/978-3-030-49342-4_23
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DOI: https://doi.org/10.1007/978-3-030-49342-4_23
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