[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/gam/jgames/v9y2018i3p52-d159547.html
   My bibliography  Save this article

Cyber–Physical Correlation Effects in Defense Games for Large Discrete Infrastructures

Author

Listed:
  • Nageswara S. V. Rao

    (Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA)

  • Chris Y. T. Ma

    (Hang Seng Management College, Hong Kong, China)

  • Fei He

    (The Department of Mechanical and Industrial Engineering, Texas A&M University, Kingsville, TX 78363, USA)

  • David K. Y. Yau

    (Department of Computer Science, Singapore University of Technology and Design, 8 Somapah Road, Singapore 487372, Singapore)

  • Jun Zhuang

    (Department of Industrial and Systems Engineering, State University of New York at Buffalo, Buffalo, NY 14260, USA)

Abstract
In certain critical infrastructures, correlations between cyber and physical components can be exploited to launch strategic attacks, so that disruptions to one component may affect others and possibly the entire infrastructure. Such correlations must be explicitly taken into account in ensuring the survival of the infrastructure. For large discrete infrastructures characterized by the number of cyber and physical components, we characterize the cyber–physical interactions at two levels: (i) the cyber–physical failure correlation function specifies the conditional survival probability of the cyber sub-infrastructure given that of the physical sub-infrastructure (both specified by their marginal probabilities), and (ii) individual survival probabilities of both sub-infrastructures are characterized by first-order differential conditions expressed in terms of their multiplier functions. We formulate an abstract problem of ensuring the survival probability of a cyber–physical infrastructure with discrete components as a game between the provider and attacker, whose utility functions are composed of infrastructure survival probability terms and cost terms, both expressed in terms of the number of components attacked and reinforced. We derive Nash equilibrium conditions and sensitivity functions that highlight the dependence of infrastructure survival probability on cost terms, correlation functions, multiplier functions, and sub-infrastructure survival probabilities. We apply these analytical results to characterize the defense postures of simplified models of metro systems, cloud computing infrastructures, and smart power grids.

Suggested Citation

  • Nageswara S. V. Rao & Chris Y. T. Ma & Fei He & David K. Y. Yau & Jun Zhuang, 2018. "Cyber–Physical Correlation Effects in Defense Games for Large Discrete Infrastructures," Games, MDPI, vol. 9(3), pages 1-24, July.
    • Handle: RePEc:gam:jgames:v:9:y:2018:i:3:p:52-:d:159547
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-4336/9/3/52/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-4336/9/3/52/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mohammad E. Nikoofal & Jun Zhuang, 2012. "Robust Allocation of a Defensive Budget Considering an Attacker's Private Information," Risk Analysis, John Wiley & Sons, vol. 32(5), pages 930-943, May.
    2. Jenelius, Erik & Westin, Jonas & Holmgren, Åke J., 2010. "Critical infrastructure protection under imperfect attacker perception," International Journal of Critical Infrastructure Protection, Elsevier, vol. 3(1), pages 16-26.
    3. Gerald Brown & Matthew Carlyle & Javier Salmerón & Kevin Wood, 2006. "Defending Critical Infrastructure," Interfaces, INFORMS, vol. 36(6), pages 530-544, December.
    4. Xiaojun Shan & Jun Zhuang, 2013. "Cost of Equity in Homeland Security Resource Allocation in the Face of a Strategic Attacker," Risk Analysis, John Wiley & Sons, vol. 33(6), pages 1083-1099, June.
    5. Kjell Hausken, 2011. "Strategic defense and attack of series systems when agents move sequentially," IISE Transactions, Taylor & Francis Journals, vol. 43(7), pages 483-504.
    6. Shan, Xiaojun & Zhuang, Jun, 2013. "Hybrid defensive resource allocations in the face of partially strategic attackers in a sequential defender–attacker game," European Journal of Operational Research, Elsevier, vol. 228(1), pages 262-272.
    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. Pramod C. Mane & Nagarajan Krishnamurthy & Kapil Ahuja, 2019. "Formation of Stable and Efficient Social Storage Cloud," Games, MDPI, vol. 10(4), pages 1-17, November.
    2. Fei He & Jun Zhuang & Nageswara S. V. Rao, 2020. "Discrete game-theoretic analysis of defense in correlated cyber-physical systems," Annals of Operations Research, Springer, vol. 294(1), pages 741-767, November.

    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. Hunt, Kyle & Zhuang, Jun, 2024. "A review of attacker-defender games: Current state and paths forward," European Journal of Operational Research, Elsevier, vol. 313(2), pages 401-417.
    2. Qingqing Zhai & Rui Peng & Jun Zhuang, 2020. "Defender–Attacker Games with Asymmetric Player Utilities," Risk Analysis, John Wiley & Sons, vol. 40(2), pages 408-420, February.
    3. Nageswara S. V. Rao & Stephen W. Poole & Chris Y. T. Ma & Fei He & Jun Zhuang & David K. Y. Yau, 2016. "Defense of Cyber Infrastructures Against Cyber‐Physical Attacks Using Game‐Theoretic Models," Risk Analysis, John Wiley & Sons, vol. 36(4), pages 694-710, April.
    4. Mohammad E. Nikoofal & Mehmet Gümüs, 2015. "On the value of terrorist’s private information in a government’s defensive resource allocation problem," IISE Transactions, Taylor & Francis Journals, vol. 47(6), pages 533-555, June.
    5. César Gil & David Rios Insua & Jesus Rios, 2016. "Adversarial Risk Analysis for Urban Security Resource Allocation," Risk Analysis, John Wiley & Sons, vol. 36(4), pages 727-741, April.
    6. Zhang, Jing & Zhuang, Jun, 2019. "Modeling a multi-target attacker-defender game with multiple attack types," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 465-475.
    7. Liang, Liang & Chen, Jingxian & Siqueira, Kevin, 2020. "Revenge or continued attack and defense in defender–attacker conflicts," European Journal of Operational Research, Elsevier, vol. 287(3), pages 1180-1190.
    8. Peiqiu Guan & Jun Zhuang, 2016. "Modeling Resources Allocation in Attacker‐Defender Games with “Warm Up” CSF," Risk Analysis, John Wiley & Sons, vol. 36(4), pages 776-791, April.
    9. Bose, Gautam & Konrad, Kai A., 2020. "Devil take the hindmost: Deflecting attacks to other defenders," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    10. Cen Song & Jun Zhuang, 2018. "Modeling Precheck Parallel Screening Process in the Face of Strategic Applicants with Incomplete Information and Screening Errors," Risk Analysis, John Wiley & Sons, vol. 38(1), pages 118-133, January.
    11. M. Hosein Zare & Oleg A. Prokopyev & Denis Sauré, 2020. "On Bilevel Optimization with Inexact Follower," Decision Analysis, INFORMS, vol. 17(1), pages 74-95, March.
    12. Zhang, Chi & Ramirez-Marquez, José Emmanuel & Wang, Jianhui, 2015. "Critical infrastructure protection using secrecy – A discrete simultaneous game," European Journal of Operational Research, Elsevier, vol. 242(1), pages 212-221.
    13. Chi Zhang & Jose Ramirez-Marquez, 2013. "Protecting critical infrastructures against intentional attacks: a two-stage game with incomplete information," IISE Transactions, Taylor & Francis Journals, vol. 45(3), pages 244-258.
    14. Adam Behrendt & Vineet M. Payyappalli & Jun Zhuang, 2019. "Modeling the Cost Effectiveness of Fire Protection Resource Allocation in the United States: Models and a 1980–2014 Case Study," Risk Analysis, John Wiley & Sons, vol. 39(6), pages 1358-1381, June.
    15. Zhang, Laobing & Reniers, Genserik & Qiu, Xiaogang, 2019. "Playing chemical plant protection game with distribution-free uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    16. Jie Xu & Jun Zhuang, 2016. "Modeling costly learning and counter-learning in a defender-attacker game with private defender information," Annals of Operations Research, Springer, vol. 236(1), pages 271-289, January.
    17. Losada, Chaya & Scaparra, M. Paola & O’Hanley, Jesse R., 2012. "Optimizing system resilience: A facility protection model with recovery time," European Journal of Operational Research, Elsevier, vol. 217(3), pages 519-530.
    18. Hunt, Kyle & Agarwal, Puneet & Zhuang, Jun, 2022. "On the adoption of new technology to enhance counterterrorism measures: An attacker–defender game with risk preferences," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    19. Vineet M. Payyappalli & Jun Zhuang & Victor Richmond R. Jose, 2017. "Deterrence and Risk Preferences in Sequential Attacker–Defender Games with Continuous Efforts," Risk Analysis, John Wiley & Sons, vol. 37(11), pages 2229-2245, November.
    20. Chen Wang & Vicki M. Bier, 2011. "Target-Hardening Decisions Based on Uncertain Multiattribute Terrorist Utility," Decision Analysis, INFORMS, vol. 8(4), pages 286-302, December.

    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:gam:jgames:v:9:y:2018:i:3:p:52-:d:159547. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.