Skip to main content

Investments in Robustness of Complex Systems: Algorithm Design

  • Conference paper
  • First Online:
Complex Networks and Their Applications XI (COMPLEX NETWORKS 2016 2022)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1078))

Included in the following conference series:

  • 1401 Accesses

Abstract

We study the problem of determining suitable investments in improving the robustness of complex systems comprising many component systems with an aim of minimizing the (time) average costs to system operators. The problem is formulated as an optimization problem that is nonconvex and challenging to solve for large systems. We propose two approaches to finding a good solution to the optimization problem: the first approach is based on a gradient method and finds a local optimizer. The second approach makes use of a convex relaxation of the original problem and provides both a lower bound on the optimal value and a feasible point. The lower bound can be used to bound the optimality gap of the solutions obtained by our methods. We provide numerical results to demonstrate the effectiveness of the proposed approaches.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 349.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 449.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 449.99
Price excludes VAT (USA)
  • Durable hardcover 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

Institutional subscriptions

Notes

  1. 1.

    Any mention of commercial products is for information only; it does not imply a recommendation or endorsement by NIST.

References

  1. Hota, A.R., Sundaram, S.: Interdependent security games on networks under behavioral probability weighting. IEEE Control Netw. Syst. 5(1), 262–273 (2018)

    Article  MATH  Google Scholar 

  2. Khalili, M.M., Zhang, X., Liu, M.: Incentivizing effort in interdependent security games using resource pooling. In: Proceedings of NetEcon (2019)

    Google Scholar 

  3. La, R.J.: Interdependent security with strategic agents and global cascades. IEEE/ACM Trans. Netw. 24(3), 1378–1391 (2016)

    Google Scholar 

  4. Lelarge, M., Bolot, J.: A local mean field analysis of security investments in networks. In: Processing of International Workshop on Economics of Networked Systems, pp. 25–30 (2008)

    Google Scholar 

  5. Cohen, R., Havlin, S., Ben-Avraham, D.: Efficient immunization strategies for computer networks and populations. Phys. Rev. Lett. 91(247901), (Dec 2003)

    Google Scholar 

  6. Borgs, C., Chayes, J., Ganesh, A., Saberi, A.: How to distributed antidote to control epidemics. Random Struct. Algorithms 37(2), 204–222 (Sept 2010)

    Google Scholar 

  7. Mai, V.S., Battou, A., Mills, K.: Distributed algorithm for suppressing epidemic spread in networks. IEEE Contr. Syst. Lett. 2(3), 555–560 (2018)

    Article  Google Scholar 

  8. Ottaviano, S., De Pellegrini, F., Bonaccorsi, S., Van Mieghem, P.: Optimal curing policy for epidemic spreading over a community network with heterogeneous population. J. Complex Networks 6(6), (Oct 2018)

    Google Scholar 

  9. Nowzari, C., Preciado, V.M., Pappas, G.J.: Optimal resource allocation for control of networked epidemic models. IEEE Control Netw. Syst. 4(2):159–169 (June 2017)

    Google Scholar 

  10. Preciado, V.M., Zargham, M., Enyioha, C., Jadbabaie, A., Pappas, G.J.: Optimal resource allocation for network protection against spreading processes. IEEE Control Netw. Syst. 1(1), 99–108 (2014)

    Article  MATH  Google Scholar 

  11. Kunreuther, H., Heal, G.: Interdependent security. J. Risk Uncertainty 26(2/3), 231–249 (2003)

    Article  MATH  Google Scholar 

  12. Mai, V.-S., La, R.J., Battou, A.: Optimal cybersecurity investments for SIS model. In: Proceeding of IEEE Globecom (2020)

    Google Scholar 

  13. Mai, V.-S., La, R.J., Battou, A.: Optimal cybersecurity investments in large networks using SIS model: algorithm design. IEEE/ACM Trans. Netw. 29(6), 2453–2466 (2021)

    Article  Google Scholar 

  14. Khanafer, A., Başar, T., Gharesifard, B.: Stability of epidemic models over directed graphs: a positive systems approach. Automatica 74, 126–134 (2016)

    Article  MATH  Google Scholar 

  15. MOSEK ApS.: The MOSEK optim. toolbox for MATLAB manual. Version 9.0. (2019). http://docs.mosek.com/9.0/toolbox/index.html

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Richard J. La .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Mai, VS., La, R.J., Battou, A. (2023). Investments in Robustness of Complex Systems: Algorithm Design. In: Cherifi, H., Mantegna, R.N., Rocha, L.M., Cherifi, C., Micciche, S. (eds) Complex Networks and Their Applications XI. COMPLEX NETWORKS 2016 2022. Studies in Computational Intelligence, vol 1078. Springer, Cham. https://doi.org/10.1007/978-3-031-21131-7_32

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-21131-7_32

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-21130-0

  • Online ISBN: 978-3-031-21131-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics