IDEAS home Printed from https://ideas.repec.org/a/eee/ijocip/v39y2022ics1874548222000567.html
   My bibliography  Save this article

The wireless network jamming problem subject to protocol interference using directional antennas and with battery capacity constraints

Author

Listed:
  • Huff, Johnathon D.
  • Leonard, William B.
  • Medal, Hugh R.

Abstract

Wireless networks support the operation and maintenance of a variety of critical infrastructure, and keeping these networks functional in the face of adversarial adversity is a paramount concern of infrastructure managers. Supporting these networks’ continued operability requires a robust understanding of wireless-network functionality, including of the ways in which adversaries may seek to jam such networks using recently developed capabilities. However, past work on wireless network jamming subject to protocol interference has focused on using omnidirectional antennas for the target and the jamming attack nodes and has not considered battery-capacity impacts on the success of these jamming efforts. Based on a field test of an ad hoc network performed by Ramanathan et al. (2005) in which the authors found that directional antennas offer an “order-of-magnitude improvement in the capacity and connectivity of an ad hoc network,” the work in this field should be extended to include directional antennas. By incorporating directional antennas, analysts may more realistically model antennas present in everyday use. In addition, battery capacity of the wireless network nodes can impact the effectiveness of a jamming attack and should be considered. By considering battery capacity, researchers are sure to take into account real-world scenarios in which energy limitations might affect actual network performance. The mathematical model discussed in this paper demonstrates the way in which network jamming is affected by directional antennas, battery capacity, and node density to determine how these factors would impact a robust jamming attack. Particularly noteworthy results include the finding that high battery capacity can offer as much as half an order of magnitude of improvement in data transmission over lower battery capacity in certain cases. These results show that the model could be used to aid decision makers in understanding how to design a network that is robust against jamming attacks.

Suggested Citation

  • Huff, Johnathon D. & Leonard, William B. & Medal, Hugh R., 2022. "The wireless network jamming problem subject to protocol interference using directional antennas and with battery capacity constraints," International Journal of Critical Infrastructure Protection, Elsevier, vol. 39(C).
  • Handle: RePEc:eee:ijocip:v:39:y:2022:i:c:s1874548222000567
    DOI: 10.1016/j.ijcip.2022.100572
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1874548222000567
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijcip.2022.100572?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. J. Cole Smith & Churlzu Lim, 2008. "Algorithms for Network Interdiction and Fortification Games," Springer Optimization and Its Applications, in: Altannar Chinchuluun & Panos M. Pardalos & Athanasios Migdalas & Leonidas Pitsoulis (ed.), Pareto Optimality, Game Theory And Equilibria, pages 609-644, Springer.
    2. Ajay Malaviya & Chase Rainwater & Thomas Sharkey, 2012. "Multi-period network interdiction problems with applications to city-level drug enforcement," IISE Transactions, Taylor & Francis Journals, vol. 44(5), pages 368-380.
    3. Kelly J. Cormican & David P. Morton & R. Kevin Wood, 1998. "Stochastic Network Interdiction," Operations Research, INFORMS, vol. 46(2), pages 184-197, April.
    4. Jose L. Walteros & Panos M. Pardalos, 2012. "Selected Topics in Critical Element Detection," Springer Optimization and Its Applications, in: Nicholas J. Daras (ed.), Applications of Mathematics and Informatics in Military Science, edition 127, chapter 0, pages 9-26, Springer.
    5. Stephen P. Borgatti, 2006. "Identifying sets of key players in a social network," Computational and Mathematical Organization Theory, Springer, vol. 12(1), pages 21-34, April.
    Full references (including those not matched with items on IDEAS)

    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. Burcu B. Keskin & Gregory J. Bott & Nickolas K. Freeman, 2021. "Cracking Sex Trafficking: Data Analysis, Pattern Recognition, and Path Prediction," Production and Operations Management, Production and Operations Management Society, vol. 30(4), pages 1110-1135, April.
    2. Matteo Fischetti & Ivana Ljubić & Michele Monaci & Markus Sinnl, 2019. "Interdiction Games and Monotonicity, with Application to Knapsack Problems," INFORMS Journal on Computing, INFORMS, vol. 31(2), pages 390-410, April.
    3. Abumoslem Mohammadi & Javad Tayyebi, 2019. "Maximum Capacity Path Interdiction Problem with Fixed Costs," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(04), pages 1-21, August.
    4. Alexander Veremyev & Oleg A. Prokopyev & Eduardo L. Pasiliao, 2014. "An integer programming framework for critical elements detection in graphs," Journal of Combinatorial Optimization, Springer, vol. 28(1), pages 233-273, July.
    5. Chen, Wei & Jiang, Manrui & Jiang, Cheng & Zhang, Jun, 2020. "Critical node detection problem for complex network in undirected weighted networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).
    6. Brian Lunday & Hanif Sherali, 2012. "Network interdiction to minimize the maximum probability of evasion with synergy between applied resources," Annals of Operations Research, Springer, vol. 196(1), pages 411-442, July.
    7. Maryam Soleimani-Alyar & Alireza Ghaffari-Hadigheh & Fatemeh Sadeghi, 2016. "Controlling Floods by Optimization Methods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4053-4062, September.
    8. Tezcan, Barış & Maass, Kayse Lee, 2023. "Human trafficking interdiction with decision dependent success," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    9. Shen, Yeming & Sharkey, Thomas C. & Szymanski, Boleslaw K. & Wallace, William (Al), 2021. "Interdicting interdependent contraband smuggling, money and money laundering networks," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    10. Claudio Contardo & Jorge A. Sefair, 2022. "A Progressive Approximation Approach for the Exact Solution of Sparse Large-Scale Binary Interdiction Games," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 890-908, March.
    11. Leonardo Lozano & J. Cole Smith, 2017. "A Backward Sampling Framework for Interdiction Problems with Fortification," INFORMS Journal on Computing, INFORMS, vol. 29(1), pages 123-139, February.
    12. Alexander Veremyev & Oleg A. Prokopyev & Eduardo L. Pasiliao, 2019. "Finding Critical Links for Closeness Centrality," INFORMS Journal on Computing, INFORMS, vol. 31(2), pages 367-389, April.
    13. Kosmas, Daniel & Sharkey, Thomas C. & Mitchell, John E. & Maass, Kayse Lee & Martin, Lauren, 2023. "Interdicting restructuring networks with applications in illicit trafficking," European Journal of Operational Research, Elsevier, vol. 308(2), pages 832-851.
    14. Ketkov, Sergey S. & Prokopyev, Oleg A., 2020. "On greedy and strategic evaders in sequential interdiction settings with incomplete information," Omega, Elsevier, vol. 92(C).
    15. Enayaty-Ahangar, Forough & Rainwater, Chase E. & Sharkey, Thomas C., 2019. "A Logic-based Decomposition Approach for Multi-Period Network Interdiction Models," Omega, Elsevier, vol. 87(C), pages 71-85.
    16. Jabarzare, Ziba & Zolfagharinia, Hossein & Najafi, Mehdi, 2020. "Dynamic interdiction networks with applications in illicit supply chains," Omega, Elsevier, vol. 96(C).
    17. Smith, J. Cole & Song, Yongjia, 2020. "A survey of network interdiction models and algorithms," European Journal of Operational Research, Elsevier, vol. 283(3), pages 797-811.
    18. Harald Held & Raymond Hemmecke & David L. Woodruff, 2005. "A decomposition algorithm applied to planning the interdiction of stochastic networks," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(4), pages 321-328, June.
    19. Mark J. O. Bagley, 2019. "Networks, geography and the survival of the firm," Journal of Evolutionary Economics, Springer, vol. 29(4), pages 1173-1209, September.
    20. Hiba Baroud & Jose E. Ramirez‐Marquez & Kash Barker & Claudio M. Rocco, 2014. "Stochastic Measures of Network Resilience: Applications to Waterway Commodity Flows," Risk Analysis, John Wiley & Sons, vol. 34(7), pages 1317-1335, July.

    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:eee:ijocip:v:39:y:2022:i:c:s1874548222000567. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/international-journal-of-critical-infrastructure-protection .

    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.