A. Becker and P. Naïm, Les réseaux bayésiens, 1999.

A. Bouejla, X. Chaze, F. Guarnieri, and A. Napoli, Bayesian networks in the management of oil field piracy risk, Risk Analysis VIII, 2012.
DOI : 10.2495/RISK120041
URL : https://hal.archives-ouvertes.fr/hal-00747392

N. Brown, Taking the Fight to the Pirates. Jane's Information Group, 2006.

J. S. Burnett, Dangerous Waters: Modern Piracy and Terror on the High Seas, 2002.

X. Chaze, A. Bouejla, F. Guarnieri, and A. Napoli, The contribution of Bayesian networks to risk management in oil field piracy, ITEMS2012, 2012.

T. Dean and K. Knazawa, A model for reasoning about persistence and causation, Computational Intelligence, vol.4, issue.2, pp.142-150, 1989.
DOI : 10.1016/0004-3702(87)90012-9

D. R. Dillon, Piracy in Asia: A Growing Barrier to Maritime Trade. Heritage Foundation Backgrounder, 2000.

M. A. Giraud, B. Alhadef, F. Guarnieri, A. Napoli, M. Bottala-gambetta et al., SARGOS : Système d'Alerte et Réponse Graduée OffShore, 2011.

B. Harris, Graph theory and its applications: proccedings, 2011.

L. D. Hudson, S. W. Bryan, S. Mahoney, and K. Blackmond, An Application of Bayesian Networks to Antiterrorism Risk Management for Military Planners Reports on Acts of Piracy and Armed Robbery Against Ships, International Maritime Organization, 2002.

B. M. Jenkins, Potential threats of offshore platforms, 1988.

K. Kalev and R. Dechter, Stochastic local search for Bayesian networks, 7th International Workshop on Artificial Intelligence and Statistics, 1999.

M. Kashubsky, Offshore energy force majeure: Nigeria's local problem with global consequences, 2008.

C. Lee and K. J. Lee, Application of Bayesian network to the probabilistic risk assessment of nuclear waste disposal, Reliability Engineering & System Safety, vol.91, issue.5, pp.5-515, 2006.
DOI : 10.1016/j.ress.2005.03.011

J. E. Martín, T. Rivas, J. M. Matías, J. Taboada, and A. Argüelles, A Bayesian network analysis of workplace accidents caused by falls from a height, Safety Science, vol.47, issue.2, pp.2-206, 2009.
DOI : 10.1016/j.ssci.2008.03.004

M. Morel and J. Broussolle, I2C, Interoperable sensors and Information sources for Common Detection of abnormal vessel behaviours and Collaborative suspect events analysis, 2011.

D. J. Nincic, Maritime Security as Energy Security: Current Threats and Challenges, Energy Security: Challenges for the 21st Century. Washington DC: Greenwood Publishing in collaboration with the Institute for the Analysis of Global Security (IAGS), 2009.

M. Ryan, Captain counts the cost of piracy, BBC News, 2006.

A. Vandecasteele and A. Napoli, Spatial ontologies for detecting abnormal maritime behaviour, 2012 Oceans, Yeosu, 2012.
DOI : 10.1109/OCEANS-Yeosu.2012.6263532
URL : https://hal.archives-ouvertes.fr/hal-00741035

C. Baoping, L. Yonghong, L. Zengkai, T. Xiaojie, Z. Yanzhen et al., Application of BayesianNetworks in Quantitative Risk Assessment of Subsea Blowout Preventer Operations. Society for Risk Analysis, pp.1-20, 2012.

J. J. Dabrowski and J. Pieter-de-villiers, Maritime piracy situation modelling with dynamic Bayesian networks Information fusion, 2013.
DOI : 10.1016/j.inffus.2014.07.001
URL : http://repository.up.ac.za/bitstream/2263/42740/1/Dabrowski_Maritime_2015.pdf

A. G. Eleye-datubo, A. Wall, and J. Wang, Marine and offshore Safety Assessment by Incorporative Risk Modelling in a Fuzzy-Bayesian Network of an Induced Mass Assignment Paradigm. Society for Risk Analysis, pp.95-112, 2008.

L. D. Hudson, B. S. Ware, S. M. Mahoney, and K. B. Laskey, An Application of Bayesian Networks to Antiterrorism Risk Management for Military Planners, p.8, 2002.

N. Khakzad, F. Khan, and P. Amyotte, Quantitative risk analysis of offshore drilling operations: A Bayesian approach, Safety Science, vol.57, pp.108-117, 2013.
DOI : 10.1016/j.ssci.2013.01.022

C. J. Lee and K. J. Lee, Application of Bayesian network to the probabilistic risk assessment of nuclear waste disposal. Reliability Engineering and System Safety, pp.515-532, 2006.

P. Leray, S. Meganck, S. Maes, and M. B. , Causal Graphical Models with Latent Variables: Learning and Inference, Innovations in Bayesian Networks: Theory and Applications, pp.219-249, 2008.
DOI : 10.1007/978-3-540-85066-3_9
URL : https://hal.archives-ouvertes.fr/hal-00412263

T. D. Nielsen and V. J. Finn, Bayesian networks and decision graphs, p.463, 2009.

J. Ren, I. Jenkinson, J. Wang, D. L. Xu, and J. B. Yang, A methodology to model causal relationships on offshore safety assessment focusing on human and organizational factors, Journal of Safety Research, vol.39, issue.1, pp.87-100, 2008.
DOI : 10.1016/j.jsr.2007.09.009

D. M. Schroeder and L. M. , Ecological and political issues surrounding decommissioning of offshore oil facilities in the Southern California Bight. Ocean and Coastel Management, pp.21-48, 2004.

P. Trucco, E. Cagno, F. Ruggeri, and O. Grande, A Bayesian Belief Network modelling of organisational factors in risk analysis : A case study in maritime transportation, Reliability Engineering and System Safety, pp.823-834, 2008.

K. Aleklett, M. Hook, K. Jakobsson, M. Lardelli, S. Snowden et al., The Peak of the Oil Age ??? Analyzing the world oil production Reference Scenario in World Energy Outlook 2008, Energy Policy, vol.38, issue.3, pp.1398-1414, 2008.
DOI : 10.1016/j.enpol.2009.11.021

B. Anifowose, M. L. Damian, H. Dan-van-der, and C. Lee, Attacks on oil transport pipelines in Nigeria: A quantitative exploration and possible explanation of observed patterns, Applied Geography, vol.32, issue.2, pp.636-651, 2012.
DOI : 10.1016/j.apgeog.2011.07.012

A. Bouejla, F. Guarnieri, and A. Napoli, A Bayesian network to manage risks of maritime piracy against offshore oil fields, Safety Science, vol.68, 2014.
DOI : 10.1016/j.ssci.2014.04.010

A. Darwiche, A differential approach to inference in Bayesian networks, Proceedings of uncertainty in Artificial Intelligence, pp.123-132, 2000.
DOI : 10.1145/765568.765570

R. Flin, K. Mearns, M. Fleming, and R. Gordon, Risk perception and safety in the offshore oil and gas industry. Health and safety executive-offshore technology report, 1996.

R. P. Gordon, R. H. Flin, K. Mearns, and M. T. Fleming, Assessing the human factors causes of accidents in the offshore oil industry. International conference on health, safety and environment in oil and gas exploration and production, pp.635-644, 1996.

S. J. Hansen, Piracy in the greater Gulf of Aden, Myths, Misconception and Remedies. Norwegian Institute for Urban and Regional Research, 2009.

M. I. Jordan, Learning in Graphical Models, 1998.
DOI : 10.1007/978-94-011-5014-9

M. I. Jordan, An Introduction to Variational Methods for Graphical Models, Machine Learning, pp.183-233, 1999.
DOI : 10.1007/978-94-011-5014-9_5

K. Kaasen, Safety Regulation of Offshore Petroleum Activities: a Study of the Legal Framework on the Norwegian Continental Shelf, 1984.

M. Kashubsky, Offshore energy force majeure: Nigeria's local problem with global consequences, 2008.

J. H. Kim and J. Pearl, A computational model for causal and diagnostic reasoning in inference engines, Proc. 8th Int. Joint Conf. on Artificial Intelligence, pp.190-193, 1983.

S. L. Lauritzen and D. J. Spiegelhalter, Local Computations with Probabilities on Graphical Structures and Their Application to Expert Systems, Journal of the Royal Statistical Society. Series B, vol.50, issue.2, pp.157-224, 1988.

K. P. Murphy, Dynamic Bayesian networks: Presentation, 2002.

J. Pearl, Causality: Models, Reasoning and Inference, 2000.
DOI : 10.1017/CBO9780511803161

H. K. White, P. Y. Hsing, W. Cho, T. M. Shank, E. E. Cordes et al., Impact of the Deepwater Horizon oil spill on a deep-water coral community in the Gulf of Mexico, Proceedings of the National Academy of Sciences, vol.109, issue.50, 2011.
DOI : 10.1073/pnas.1118029109

C. Wright, A fallible safety system: institutionalised irrationality in the offshore oil and gas industry. The sociological review, pp.79-103, 1994.

M. Bouissou and B. Bourreau, Revue des applications des réseaux bayésiens dynamiques en analyse des risques, 18ème Congrès de Maîtrise des Risques et Sûreté de Fonctionnement, pp.16-18, 2012.

J. J. Dabrowski and J. Pieter-de-villiers, Maritime Piracy Situation Modelling with Dynamic Bayesian Networks. Papers submitted to Information Fusion, 2013.

A. Darwiche, A differential approach to inference in Bayesian networks, Journal of the ACM, vol.50, issue.3, pp.123-132, 2000.
DOI : 10.1145/765568.765570

A. Darwiche, Modeling and Reasoning with Bayesian Networks, 2009.
DOI : 10.1017/CBO9780511811357

B. Efron, Large scale inference: Empirical Bayes methods for estimation, testing, and prediction, 2010.
DOI : 10.1017/CBO9780511761362

O. François, De l'identification de structure de réseaux bayésiens à la reconnaissance des formes à partir d'informations complètes ou incomplètes, 2006.

N. Friedman and M. Goldszmidt, Learning Bayesian Networks with Local Structure. Learning in graphical models, NATO ASI Series, pp.421-459, 1998.

G. M. Alhadef, B. Guarnieri, F. Napoli, A. , B. Gambetta et al., SARGOS: Securing Offshore Infrastructures Through a Global Alert and Graded Response, pp.27-29, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00660219

D. Heckerman, C. Meek, and G. Cooper, A Bayesian Approach to Causal Discovery, technical report, 1997.
DOI : 10.1007/3-540-33486-6_1

D. Heckerman, A tutorial on learning with Bayesian network, M.I Jordan, learning in graphical models, pp.301-351, 1999.

M. I. Jordan, Learning in Graphical Models. The Netherlands, 1998.

M. Kashubsky, Offshore energy force majeure: Nigeria's local problem with global consequences. Maritime studies, 2008.

H. Langseth and O. Bangso, Parameter learning in object-oriented Bayesian networks, Annals of Mathematics and Artificial Intelligence, vol.32, issue.1/4, pp.221-243, 2001.
DOI : 10.1023/A:1016769618900

R. J. Little, Calibrated Bayes, The American Statistician, vol.60, issue.3, pp.213-223, 2006.
DOI : 10.1198/000313006X117837

S. Meganck, P. Laray, and B. Manderick, Learning causal Bayesian Networks from observations and experiments: A decision theoretic approach. Modeling decisions for artificial intelligence, lecture notes in computer science, pp.58-69, 2006.

M. Morel, M. P. Gleizes, A. Napoli, A. Littaye, V. Bazin et al., ScanMaris: an Adaptive and Integrative Approach for Wide Maritime Zone Surveillance, Cognitive Systems with Interactive Sensors, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00747879

P. Mukundan, Piracy and armed robbery against ships today, WMU Journal of Maritime Affairs, vol.2, issue.2, pp.167-180, 2003.
DOI : 10.1007/BF03195042

P. Naïm, P. H. Wuillemin, P. Leray, O. Pourret, and A. Becker, Réseaux Bayésiens, pp.2-212, 2004.

R. E. Neapolitan, Probabilistic Reasoning In Expert Systems: Theory and Algorithms, 2012.

T. D. Nielsen and J. F. Verner, Bayesian Networks and Decisions Graphs, Series Information Science and Statistics, 2007.

D. J. Nincic, Maritime Security as Energy Security: Current Threats and Challenges Energy Security: Challenges for the 21st Century, in collaboration with the Institute for the Analysis of Global Security (IAGS), 2009.

F. Onuoha, Sea piracy and maritime security in the Horn of Africa: The Somali coast and Gulf of Aden in perspective, African Security Review, vol.4, issue.3, pp.31-44, 2010.
DOI : 10.1080/03056240802569268

J. Pearl, Causality: Models, Reasoning and Inference, 2000.
DOI : 10.1017/CBO9780511803161

P. Trucco, E. Cagno, F. Ruggeri, and O. Grande, A Bayesian Belief Network modelling of organizational factors in risk analysis: A case study in maritime transportation, Reliability Engineering and System Safety, pp.823-834, 2008.

A. Antonucci and M. And-zaffalon, Decision-theoretic specification of creedal networks : A unified language for uncertain modelling with sets of bayesian networks; international journal of approximate reasoning, pp.345-361, 2008.

B. Bachimont, Qu'est-ce qu'une ontologie, 2006.

T. Bayes, AN ESSAY TOWARDS SOLVING A PROBLEM IN THE DOCTRINE OF CHANCES, Biometrika, vol.45, issue.3-4, pp.370-418, 1763.
DOI : 10.1093/biomet/45.3-4.296

A. Becker and P. Naïm, Les réseaux bayésiens, 1999.

A. Bouejla, X. Chaze, A. Napoli, F. Guarnieri, T. Eude et al., Contribution des réseaux bayésiens à la gestion du risque de piraterie contre les champs pétroliers. Workshop Interdisciplinaire sur la sécurité globale, 2012.

A. Bouejla, X. Chaze, F. Guarnieri, and A. Napoli, Conception d'un réseau bayésien pour la prévention du risque de piraterie contre les champs pétroliers, Journées francophones sur les réseaux bayésiens, îles Kerkennah, pp.11-13, 2012.

A. Bouejla, X. Chaze, A. Napoli, and F. Guarnieri, Application des réseaux bayésiens à la planification de la réponse à une attaque de pirates contre un champ pétrolier, Informatique des organisations et Systèmes d'Information et de Décision, pp.29-31, 2012.

A. Bouejla, X. Chaze, F. Guarnieri, and A. Napoli, Apports des réseaux bayésiens pour la sûreté et la mise en sécurité des infrastructures pétrolières offshore, 2012.

A. Bouejla, F. Guarnieri, and A. Napoli, Apports des réseaux bayésiens « dynamiques » à la lutte contre la piraterie maritime. Lambda mu 19, 2014.

A. Bouejla, X. Chaze, F. Guarnieri, and A. Napoli, A Bayesian network to manage risks of maritime piracy against offshore oil fields, Safety Science, vol.68, pp.222-230, 2014.
DOI : 10.1016/j.ssci.2014.04.010

M. Bouissou and B. Bourreau, Revue des applications des réseaux bayésiens dynamiques en analyse des risques, 18ème Congrès de Maîtrise des Risques et Sûreté de Fonctionnement, pp.16-18, 2012.

N. Brown, Taking the Fight to the Pirates. Jane's Information Group, 2006.

J. S. Burnett, Dangerous Waters: Modern Piracy and Terror on the High Seas, 2002.

F. Castaldo, F. A. Palmieri, V. Bastani, L. Marcenaro, and C. Regazzoni, Abnormal vessel behavior detection in port areas based on dynamic bayesian network, 17th IEEE International Conference on Information Fusion, 2014.

X. Chaze, A. Bouejla, A. Napoli, F. Guarnieri, T. Eude et al., The contribution of bayesian networks to manage risks of maritime piracy against oil offshore fields. Information technologies for the maritime sectors, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00734351

X. Chaze, A. Bouejla, A. Napoli, and F. Guarnieri, Integration of a bayesian network for response planning in a maritime piracy risk management system. System of systems engineering, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00734748

X. Chaze, A. Bouejla, F. Guarnieri, and A. Napoli, Causal Probabilistic Modeling with Bayesian Networks to Combat the Risk of Piracy against Offshore Oil Platforms. The Radio science Bulletin, Disaster Management special issue, pp.21-34, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00856707

J. J. Dabrowski and J. Pieter-de-villiers, Maritime piracy situation modelling with dynamic Bayesian networks Information fusion, 2013.

P. A. Dagum, M. Chavez, and R. , Approximating probabilistic inference in Bayesian belief networks, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.15, issue.3, pp.246-256, 1993.
DOI : 10.1109/34.204906

D. , B. Shachter, R. D. , D. Favero, and B. A. , Symbolic probabilistic inference in belief networks, pp.90-126, 1990.

A. Darwiche, A differential approach to inference in Bayesian networks, Journal of the ACM, vol.50, issue.3, pp.123-132, 2000.
DOI : 10.1145/765568.765570

A. Darwiche, Constant-space reasoning in dynamic Bayesian networks, International Journal of Approximate Reasoning, vol.26, issue.3, pp.161-178, 2001.
DOI : 10.1016/S0888-613X(00)00067-0

A. Darwiche, Modeling and Reasoning with Bayesian Networks, 2009.
DOI : 10.1017/CBO9780511811357

T. Dean and K. Knazawa, A model for reasoning about persistence and causation, Computational Intelligence, vol.4, issue.2, pp.142-150, 1989.
DOI : 10.1016/0004-3702(87)90012-9

A. Dempster, N. Laird, and D. Rubin, Maximum likelihood from incomplete data via the EM algorithm, Journal of the royal statistical society, vol.39, pp.1-38, 1977.

D. R. Dillon, Piracy in Asia: A Growing Barrier to Maritime Trade. Heritage Foundation Backgrounder, 2000.

B. Efron, Bayesians, Frequentists, and Scientists, Journal of the American Statistical Association, vol.100, issue.469, pp.1-5, 2005.
DOI : 10.1198/016214505000000033

B. Efron, Large scale inference: Empirical Bayes methods for estimation, testing, and prediction, 2010.
DOI : 10.1017/CBO9780511761362

R. Flin, K. Mearns, M. Fleming, and R. Gordon, Risk perception and safety in the offshore oil and gas industry. Health and safety executive-offshore technology report, 1996.

O. François, De l'identification de structure de réseaux bayésiens à la reconnaissance des formes à partir d'informations complètes ou incomplètes, 2006.

N. Friedman, The bayesian structural EM algorithm, proceedings of the 14 th conference on uncertainty in artificial intelligence, pp.129-138, 1998.

N. Friedman and M. Goldszmidt, Learning Bayesian Networks with Local Structure. Learning in graphical models, NATO ASI Series, pp.421-459, 1998.

N. Friedman, I. Nachman, and D. Peer, Learning of bayesian network structure from massive datasets : the sparse candidate algorithm, proceedings of the 15 th conference on uncertainty in artificial intelligence, pp.206-215, 1999.

G. M. , V. Gaver, A. Napoli, A. Scapel, C. Chaumartin et al., SARGOS : Système d'Alerte et de Réponse Graduée OffShore, 2010.

M. A. Giraud, B. Alhadef, F. Guarnieri, A. Napoli, M. Bottala-gambetta et al., SARGOS : Système d'Alerte et Réponse Graduée OffShore, 2011.

M. A. Giraud, B. Alhadef, F. Guarnieri, A. Napoli, M. Bottala-gambetta et al., SARGOS : Système d'Alerte et Réponse Graduée OffShore. Workshop interdisciplinaire sur la sécurité globale, 2012.

S. J. Hansen, Piracy in the greater Gulf of Aden, Myths, Misconception and Remedies, Norwegian Institute for Urban and Regional Research, 2009.

B. Harris, Graph theory and its applications: proccedings, 2011.

D. Heckerman, C. Meek, and G. Cooper, A Bayesian Approach to Causal Discovery, technical report, 1997.
DOI : 10.1007/3-540-33486-6_1

D. Heckerman, A tutorial on learning with Bayesian network, M.I Jordan, learning in graphical models, pp.301-351, 1999.

L. D. Hudson, S. W. Bryan, S. Mahoney, and K. Blackmond, An Application of Bayesian Networks to Antiterrorism Risk Management for Military Planners, 2002.

B. M. Jenkins, Potential threats of offshore platforms, 1988.

F. Jensen, Introduction to Bayesian Networks, 1996.

M. I. Jordan, Learning in Graphical Models. The Netherlands, 1998.

M. I. Jordan, Learning in Graphical Models, 1998.
DOI : 10.1007/978-94-011-5014-9

M. I. Jordan, An Introduction to Variational Methods for Graphical Models, Machine Learning, pp.183-233, 1999.
DOI : 10.1007/978-94-011-5014-9_5

M. Jordan, Graphical Models, Statistical Science, vol.19, issue.1, pp.140-155, 2004.
DOI : 10.1214/088342304000000026

K. Kaasen, Safety Regulation of Offshore Petroleum Activities: a Study of the Legal Framework on the Norwegian Continental Shelf, 1984.

K. Kalev and R. Dechter, Stochastic local search for Bayesian networks, 7th International Workshop on Artificial Intelligence and Statistics, 1999.

M. Kashubsky, Offshore energy force majeure: Nigeria's local problem with global consequences, 2008.

N. Khakzad, F. Khan, and P. Amyotte, Quantitative risk analysis of offshore drilling operations: A Bayesian approach, Safety Science, vol.57, pp.108-117, 2013.
DOI : 10.1016/j.ssci.2013.01.022

J. H. Kim and J. Pearl, A computational model for causal and diagnostic reasoning in inference engines, Proc. 8th Int. Joint Conf. on Artificial Intelligence, pp.190-193, 1983.

J. Kim and J. Pearl, Convince: A Conversational Inference Consolidation Engine, IEEE Transactions on Systems, Man, and Cybernetics, vol.17, issue.2, pp.120-132, 1987.
DOI : 10.1109/TSMC.1987.4309025

J. H. Koskinen and T. A. Snijders, Bayesian inference for dynamic social network data, Journal of Statistical Planning and Inference, vol.137, issue.12, pp.3930-3938, 2007.
DOI : 10.1016/j.jspi.2007.04.011

P. Leray, Réseaux bayésiens : apprentissage et modélisation de systems complexes. Habilitation à diriger les recherché, 2006.

R. J. Little, Calibrated Bayes, The American Statistician, vol.60, issue.3, pp.213-223, 2006.
DOI : 10.1198/000313006X117837

M. Morel, A. Napoli, J. P. George, F. Jangal, M. A. Giraud et al., Surveillance et contrôle des activités des navires en mer. Workshop interdisciplinaire sur la sécurité globale, 2010.

M. Morel, A. Napoli, A. Littaye, J. P. Georgé, and F. Jangal, Surveillance et contrôle des activités des navires en mer. Workshop interdisciplinaire sur la sécurité globale, 2008.

M. Morel and J. Broussolle, I2C, Interoperable sensors and Information sources for Common Detection of abnormal vessel behaviours and Collaborative suspect events analysis, 2011.

P. Mukundan, Piracy and armed robbery against ships today, WMU Journal of Maritime Affairs, vol.2, issue.2, pp.167-180, 2003.
DOI : 10.1007/BF03195042

K. P. Murphy, Y. Weiss, and M. Jordan, Loopy belief propagation for approximate inference : An empirical study, proceeding of the fifteenth annual conference on uncertainty in artificial intelligence, pp.467-475, 1999.

K. P. Murphy and Y. Weiss, The factored frontier algorithm for approximate inference in dynamic bayesian networks, 2001.

P. Naïm, H. Wuillemin, P. Leray, O. Pourret, and A. Becker, Réseaux bayésiens. Eyrolles, 3ème édition, pp.978-980, 1999.

P. Naïm, P. H. Wuillemin, P. Leray, O. Pourret, and A. Becker, Réseaux Bayésiens, pp.2-212, 2004.

A. Napoli, Sécurité et sûreté de la maritimisation de l'énergie, pp.23-25, 2014.

E. Neapolitan, Learning Bayesian Networks, p.130125342, 2003.
DOI : 10.1016/B978-012370477-1.50021-9

R. E. Neapolitan, Probabilistic Reasoning In Expert Systems: Theory and Algorithms, 2012.

T. D. Nielsen and J. F. Verner, Bayesian Networks and Decisions Graphs, Series Information Science and Statistics, 2007.

T. D. Nielsen and V. J. Finn, Bayesian networks and decision graphs, 2009.

D. Nikoski, Learning stationary temporal probabilistic networks, conference on automated learning and discovery, 1998.

F. Onuoha, Sea piracy and maritime security in the Horn of Africa: The Somali coast and Gulf of Aden in perspective, African Security Review, vol.4, issue.3, pp.31-44, 0191.
DOI : 10.1080/03056240802569268

J. Pearl, Causality: Models, Reasoning and Inference, 2000.
DOI : 10.1017/CBO9780511803161

J. F. Pichard, Approche épistémologique et diverses conceptions de la probabilité, Reperes- IREM, issue.32, 1998.

L. R. Rabiner, Atutorial on hidden markov models and selected applications in speech recognition, Proceedings of the IEEE, 1989.

M. Riveiro, G. Falkman, T. Ziemke, and H. Warston, VISAD: an interactive and visual analytical tool for the detection of behavioral anomalies in maritime traffic data, Visual Analytics for Homeland Defense and Security, 2009.
DOI : 10.1117/12.817819

M. Ryan, Captain counts the cost of piracy, BBC News, 2006.

. Saab-groupe, Sea Giraffe AMB multi-rôle naval surveillance radar, 2005.

. Sagem, SAGEM l'excellence en optronique, avionique, électronique et logiciels critique, 2012.

D. M. Schroeder and L. M. , Ecological and political issues surrounding decommissioning of offshore oil facilities in the Southern California Bight. Ocean and Coastel Management, pp.21-48, 2004.

P. Spirtes, C. Glymour, and R. Scheines, Causation, prediction, and search, 1993.
DOI : 10.1007/978-1-4612-2748-9

A. Stephenson, An introduction to bayesian network theory and usage, pp.0-03, 2000.

A. Vandecasteele, R. Devillers, and A. Napoli, From Movement Data to Objects Behavior Using Semantic Trajectory and Semantic Events, Marine Geodesy, vol.15, issue.7, pp.126-144, 2014.
DOI : 10.1007/978-3-642-04947-7_41
URL : https://hal.archives-ouvertes.fr/hal-01002799

T. Verma and J. And, Equivalence and synthesis of causal models, 1991.

J. Wainwright and M. Jordan, Graphical Models, Exponential Families, and Variational Inference, Machine Learning, pp.1-305, 2008.
DOI : 10.1561/2200000001

C. Wright, A fallible safety system: institutionalised irrationality in the offshore oil and gas industry. The sociological review, pp.79-103, 1994.

D. Yergin, Ensuring Energy Security, Foreign Affairs, 2006.

C. Yuan and M. J. Druzdzel, Importance sampling algorithms for bayesian networks : principles and performance. Mathematical and computer modelling, pp.1189-1207, 2006.

L. Zhang, A simple approach to Bayesian network computations, Proc. Of the Trenth Canadian Conference on Artificial Intelligence, pp.171-178, 1994.