IDEAS home Printed from https://ideas.repec.org/a/taf/jriskr/v19y2016i7p894-912.html
   My bibliography  Save this article

Modeling current and emerging threats in the airport domain through adversarial risk analysis

Author

Listed:
  • Javier Cano
  • Alessandro Pollini
  • Lorenzo Falciani
  • Uğur Turhan

Abstract

Airports are critical infrastructures entailing intense human, commercial and economic activity. As such, they are preferred targets for criminal and terrorist groups, who are attracted by the promisingly high revenues they might get from an attack. Every year, airport authorities worldwide have to face, with limited resources, attacks arising from different adversaries. There are several sensible areas within an airport organization that are especially vulnerable to the terrorist threat, including, among others: (1) those related to human lives (of passengers or staff); (2) airport infrastructure (airport perimeter, main terminal, Air Traffic Control Tower, runways, hangars, etc.); (3) aircrafts and other ground vehicles; and (4) IT systems and services. Besides the more traditional ones, we are particularly concerned with attacks launched against the last type of targets, an emerging and increasingly worrisome threat. Specifically, we analyze the impact of cyber-attacks launched by organized groups whose main goal is to take hold of airport operations. In some cases, in order to have more chances to achieve their purpose (and take advantage of its eventual success), cyber attackers may be backed up by a terrorist group who will try to interfere with the Air Traffic Management network. In this paper, we aim at supporting airport authorities in their fight against both threats, by devising a security allocation plan. We provide an adversarial risk analysis model to address the problem, and apply it to obtain the optimal portfolio of preventive measures in an illustrative case study. The model is open to extensions, as e.g. larger and more complex technical infrastructures, new threats, or additional recovery measures deployed by different defensive agents.

Suggested Citation

  • Javier Cano & Alessandro Pollini & Lorenzo Falciani & Uğur Turhan, 2016. "Modeling current and emerging threats in the airport domain through adversarial risk analysis," Journal of Risk Research, Taylor & Francis Journals, vol. 19(7), pages 894-912, August.
  • Handle: RePEc:taf:jriskr:v:19:y:2016:i:7:p:894-912
    DOI: 10.1080/13669877.2015.1057201
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/13669877.2015.1057201
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/13669877.2015.1057201?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Anders A F Wahlberg & Lennart Sjoberg, 2000. "Risk perception and the media," Journal of Risk Research, Taylor & Francis Journals, vol. 3(1), pages 31-50, January.
    2. Stern, Jessica & Wiener, Jonathan B., 2006. "Precaution against Terrorism," Working Paper Series rwp06-019, Harvard University, John F. Kennedy School of Government.
    3. Olja Čokorilo & Mario De Luca & Gianluca Dell’Acqua, 2014. "Aircraft safety analysis using clustering algorithms," Journal of Risk Research, Taylor & Francis Journals, vol. 17(10), pages 1325-1340, November.
    4. Basak, Suleyman & Shapiro, Alexander, 2001. "Value-at-Risk-Based Risk Management: Optimal Policies and Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 14(2), pages 371-405.
    5. Terje Aven & Ortwin Renn, 2009. "On risk defined as an event where the outcome is uncertain," Journal of Risk Research, Taylor & Francis Journals, vol. 12(1), pages 1-11, January.
    6. Urs Steiner Brandt, 2014. "The implication of extreme events on policy responses," Journal of Risk Research, Taylor & Francis Journals, vol. 17(2), pages 221-240, February.
    7. Jessica Stern & Jonathan B. Wiener, 2006. "Precaution Against Terrorism," Journal of Risk Research, Taylor & Francis Journals, vol. 9(4), pages 393-447, June.
    8. Pacheco, Ricardo Rodrigues & Fernandes, Elton & Domingos, Eduardo Marques, 2014. "Airport airside safety index," Journal of Air Transport Management, Elsevier, vol. 34(C), pages 86-92.
    9. Susanne Rippl, 2002. "Cultural theory and risk perception: a proposal for a better measurement," Journal of Risk Research, Taylor & Francis Journals, vol. 5(2), pages 147-165, April.
    10. Barry C. Ezell & R. Michael Robinson & Peter Foytik & Craig Jordan & David Flanagan, 2013. "Cyber risk to transportation, industrial control systems, and traffic signal controllers," Environment Systems and Decisions, Springer, vol. 33(4), pages 508-516, December.
    11. Insua, Insua Rios & Rios, Jesus & Banks, David, 2009. "Adversarial Risk Analysis," Journal of the American Statistical Association, American Statistical Association, vol. 104(486), pages 841-854.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wei Wang & Francesco Di Maio & Enrico Zio, 2019. "Adversarial Risk Analysis to Allocate Optimal Defense Resources for Protecting Cyber–Physical Systems from Cyber Attacks," Risk Analysis, John Wiley & Sons, vol. 39(12), pages 2766-2785, December.
    2. Eric DuBois & Ashley Peper & Laura A. Albert, 2023. "Interdicting Attack Plans with Boundedly Rational Players and Multiple Attackers: An Adversarial Risk Analysis Approach," Decision Analysis, INFORMS, vol. 20(3), pages 202-219, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jamie K. Wardman & Gabe Mythen, 2016. "Risk communication: against the Gods or against all odds? Problems and prospects of accounting for Black Swans," Journal of Risk Research, Taylor & Francis Journals, vol. 19(10), pages 1220-1230, November.
    2. John D. Graham & Jonathan B. Wiener, 2008. "The precautionary principle and risk--risk tradeoffs: a comment," Journal of Risk Research, Taylor & Francis Journals, vol. 11(4), pages 465-474, June.
    3. Kjell Hausken, 2019. "Principal–Agent Theory, Game Theory, and the Precautionary Principle," Decision Analysis, INFORMS, vol. 16(2), pages 105-127, June.
    4. Domenico Tosini, 2021. "Social immunology: A theory of the immune processes of social systems," Systems Research and Behavioral Science, Wiley Blackwell, vol. 38(1), pages 50-60, January.
    5. Charles Vlek, 2013. "How Solid Is the Dutch (and the British) National Risk Assessment? Overview and Decision‐Theoretic Evaluation," Risk Analysis, John Wiley & Sons, vol. 33(6), pages 948-971, June.
    6. Steve Jacob & Nathalie Schiffino, 2015. "Risk Policies in the United States: Definition and Characteristics Based on a Scoping Review of the Literature," Risk Analysis, John Wiley & Sons, vol. 35(5), pages 849-858, May.
    7. Carl F. Cranor & Adam M. Finkel, 2018. "Toward the usable recognition of individual benefits and costs in regulatory analysis and governance," Regulation & Governance, John Wiley & Sons, vol. 12(1), pages 131-149, March.
    8. Gao, Kaiye & Yan, Xiangbin & Liu, Xiang-dong & Peng, Rui, 2019. "Object defence of a single object with preventive strike of random effect," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 209-219.
    9. Jaap C. Hanekamp & Aalt Bast, 2008. "Why RDAs and ULs Are Incompatible Standards in the U‐Shape Micronutrient Model: A Philosophically Orientated Analysis of Micronutrients' Standardizations," Risk Analysis, John Wiley & Sons, vol. 28(6), pages 1639-1652, December.
    10. Randall, Alan, 2009. "We Already Have Risk Management - Do We Really Need the Precautionary Principle?," International Review of Environmental and Resource Economics, now publishers, vol. 3(1), pages 39-74, August.
    11. Gordon J. Alexander & Alexandre M. Baptista, 2004. "A Comparison of VaR and CVaR Constraints on Portfolio Selection with the Mean-Variance Model," Management Science, INFORMS, vol. 50(9), pages 1261-1273, September.
    12. Li, Xiao-Ming & Rose, Lawrence C., 2009. "The tail risk of emerging stock markets," Emerging Markets Review, Elsevier, vol. 10(4), pages 242-256, December.
    13. Ke Zhou & Jiangjun Gao & Duan Li & Xiangyu Cui, 2017. "Dynamic mean–VaR portfolio selection in continuous time," Quantitative Finance, Taylor & Francis Journals, vol. 17(10), pages 1631-1643, October.
    14. Juan Carlos Escanciano & Zaichao Du, 2015. "Backtesting Expected Shortfall: Accounting for Tail Risk," CAEPR Working Papers 2015-001, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    15. Giovanni Bonaccolto & Massimiliano Caporin & Sandra Paterlini, 2018. "Asset allocation strategies based on penalized quantile regression," Computational Management Science, Springer, vol. 15(1), pages 1-32, January.
    16. Rostagno, Luciano Martin, 2005. "Empirical tests of parametric and non-parametric Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) measures for the Brazilian stock market index," ISU General Staff Papers 2005010108000021878, Iowa State University, Department of Economics.
    17. Boon, L.N. & Brière, M. & Rigot, S., 2018. "Regulation and pension fund risk-taking," Journal of International Money and Finance, Elsevier, vol. 84(C), pages 23-41.
    18. Dong, Yinghui & Zheng, Harry, 2019. "Optimal investment of DC pension plan under short-selling constraints and portfolio insurance," Insurance: Mathematics and Economics, Elsevier, vol. 85(C), pages 47-59.
    19. Christophe Boucher & Benjamin Hamidi & Patrick Kouontchou & Bertrand Maillet, 2012. "Une évaluation économique du risque de modèle pour les investisseurs de long terme," Revue économique, Presses de Sciences-Po, vol. 63(3), pages 591-600.
    20. Alexander, Gordon J. & Baptista, Alexandre M. & Yan, Shu, 2012. "When more is less: Using multiple constraints to reduce tail risk," Journal of Banking & Finance, Elsevier, vol. 36(10), pages 2693-2716.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:jriskr:v:19:y:2016:i:7:p:894-912. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RJRR20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.