Skip to main content

The Contribution of Bayesian Networks to Manage Risks of Maritime Piracy against Oil Offshore Fields

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNISA,volume 7240)

Abstract

In recent years pirate attacks against shipping and oil fields have continued to increase in quantity and severity. For example, the attack against the Exxon Mobil oil rig in 2010 off the coast of Nigeria ended in the kidnap of 19 crew members and a reduction in daily oil production of 45,000 barrels, which resulted in an international rise in the price of oil. This example is a perfect illustration of current weaknesses in existing anti-piracy systems. The SARGOS project proposes an innovative system to address this problem. It takes into account the entire threat treatment process; from the detection of a potential threat to implementation of the response. The response to an attack must take into account all of the many parameters related to the threat, the potential target, the available protection resources, environmental constraints, etc. To manage these parameters, the power of Bayesian networks is harnessed to identify potential countermeasures and the means to manage them.

Keywords

  • Bayesian Network
  • International Maritime Organization
  • Crew Member
  • Response Plan
  • Attack Scenario

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (Canada)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (Canada)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (Canada)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Giraud, M.A., Alhadef, B., Guarnieri, F., Napoli, A., Bottala Gambetta, M., Chaumartin, D., Philips, M., Morel, M., Imbert, C., Itcia, E., Bonacci, D., Michel, P.: SARGOS: Securing Offshore Infrastructures Through a Global Alert and Graded Response. In: System Workshop MAST Europe, Juin 27-29 (2011)

    Google Scholar 

  2. Giraud, M.A., Alhadef, B., Guarnieri, F., Napoli, A., Bottala Gambetta, M., Chaumartin, D., Philips, M., Morel, M., Imbert, C., Itcia, E., Bonacci, D., Michel, P.: SARGOS: Système d’Alerte et Réponse Graduèe Off Shore. In: Conference WISG, Janvier 25-26 (2011)

    Google Scholar 

  3. Giraud, M.A., Van Gaver, A., Napoli, A., Scapel, C., Chaumartin, D., Morel, M., Itcia, E., Bonacci, D.: SARGOS: Système d’Alerte et Réponse Graduèe Off Shore. In: Conference WISG, Janvier 26-27 (2010)

    Google Scholar 

  4. Ware, B.S., Beverina, A.F., Gong, L., Colder, B.: A Risk-Based Decision Support System for Antiterrorism. Digital Sandbox, 8 pages (Août 14, 2002)

    Google Scholar 

  5. Naïm, P., Wuillemin, P.H., Leray, P., Pourret, O., Becker, A.: Les réseaux bayésiens 3, 424 pages (1999)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Chaze, X., Bouejla, A., Napoli, A., Guarnieri, F., Eude, T., Alhadef, B. (2012). The Contribution of Bayesian Networks to Manage Risks of Maritime Piracy against Oil Offshore Fields. In: Yu, H., Yu, G., Hsu, W., Moon, YS., Unland, R., Yoo, J. (eds) Database Systems for Advanced Applications. DASFAA 2012. Lecture Notes in Computer Science, vol 7240. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29023-7_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-29023-7_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29022-0

  • Online ISBN: 978-3-642-29023-7

  • eBook Packages: Computer ScienceComputer Science (R0)