Generalized model of spectrally selective destructive impacts on special-purpose optical transport networks

A. P. Boiko¹, S. M. Odoevsky¹, Y. I. Starodubtsev¹

¹Military Academy of Communications named after Marshal of the Soviet Union S.M. Budyonny.
194064, Russia, Saint-Petersburg, Tihoreckiy prospekt, 3.

DOI 10.24412/2410-9916-2026-4-001-052

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Abstract

Problem statement. The development of the concept of shared use of spectral resources in fiber-optic communication links, including "Optical Spectrum as a Service", raises issues of ensuring the security and resilience of optical transport networks when independent users are granted access to separate portions of the optical spectrum. Restrictions on the spectrum and power of user signals do not eliminate the possibility of affecting other users' channels due to the generation of four-wave mixing products. Therefore, there is a need to assess potential damage and determine the most harmful configurations of attacking optical signals. Objective. The objective of this study is to develop a generalized mathematical model of spectrally selective destructive impacts that enables the maximum damage to target optical channels to be determined under the adversary's limited spectral and power resources. Methods. The methods used include mathematical modeling of four-wave mixing, mixed-integer nonlinear programming, and the spatial branch-and-bound method. The aggregate data rate of blocked optical channels is used as the damage metric. Novelty. A generalized model of spectrally selective destructive impacts is developed. The model is represented as a nested family of specific models corresponding to a successive expansion of an adversary's capabilities to control the average power, center frequency, and spectral width of attacking optical signals. The model accounts for the out-of-band impact of four-wave mixing products on target optical channels. Result. The computational experiment has shown that expanding the adversary's capabilities to control the spectral and power parameters of attacking optical signals generally increases the maximum achievable damage to target optical channels. Practical significance. The developed generalized model can be used to assess the vulnerability of optical transport networks and to substantiate requirements for monitoring the parameters of user optical signals when fiber-optic link spectrum resources are shared.

Key words

optical transport network, spectral resource, destructive impact, four-wave mixing, nonlinear effects, OSNR, mathematical modeling, spatial branch-and-bound method.

Reference for citation

Boiko A. P., Odoevsky S. M., Starodubtsev Y. I. Generalized model of spectrally selective destructive impacts on special-purpose optical transport networks. Systems of Control, Communication and Security, 2026, no. 4, pp. 1-52 (in Russian). DOI: 10.24412/2410-9916-2026-4-001-052

References

1. Boyko A. P., Odoevsky S. M., Starodubtsev Yu. I. Povyshenie propusknosi sposobnosti opticheskikh transportnykh setei spetsial'nogo naznacheniia za schet effektivnogo ispol'zovaniia arenduemykh spektral'nykh resursov. Voprosy oboronnoi tekhniki. Seriia 16: Tekhnicheskie sredstva protivodeistviia terrorizmu, 2025, no. 3-4 (201-202), pp. 85-92 (in Russian).

2. Makarenko S. I. Modeli sistemy sviazi v usloviiakh prednamerennykh destabiliziruiushchikh vozdeistvii i vedeniia razvedki [Models of communication systems under intentional destabilizing impacts and intelligence operations]. Saint Petersburg, Naukoemkie Tekhnologii Publ., 2020. 337 p. (In Russian).

3. Resilience, civil preparedness and Article 3. North Atlantic Treaty Organization (NATO), 2024. Available at: https://www.nato.int/en/what-we-do/deterrence-and-defence/resilience-civil-preparedness-and-article-3 (accessed 23 August 2026).

4. The Telecom Sector's Contribution to Europe's Security and Resilience. Copenhagen Economics; commissioned by Connect Europe, 2025. 42 p. Available at: https://connecteurope.org/sites/default/files/2025-10/Resilience%20and%20security%20study_CopenhagenEconomics%20for%20Connect%20Europe_Oct2025.pdf (accessed 23 August 2026).

5. Kaeval K., Grobe K., Elbers J.-P. Operation of optical spectrum as a service in disaggregated and multi-operator environments [Invited]. Journal of Optical Communications and Networking, 2025, vol. 17, no. 1, pp. A46-A58. DOI: 10.1364/JOCN.534118.

6. Kaeval K., Grobe K., Elbers J.-P., Griesser H., Eiselt M., Autenrieth A. Characterization of the optical spectrum as a service. Journal of Optical Communications and Networking, 2022, vol. 14, no. 5, pp. 398-410. DOI: 10.1364/JOCN.454158.

7. Boiko A. P., Odoevsky S. M., Yasinsky S. A. Model of destructive impacts based on nonlinear effects in fiber-optic communication lines with a flexible frequency grid. Elektrosvyaz, 2026, no. 4, pp. 15-24. DOI: 10.34832/ELSV.2026.78.4.002 (In Russian).

8. Dahan D., Mahlab U. Security threats and protection procedures for optical networks. IET Optoelectronics, 2017, vol. 11, pp. 186-200. DOI: 10.1049/iet-opt.2016.0150.

9. Skorin-Kapov N., Furdek M., Zsigmond S., Wosinska L. Physical-layer security in evolving optical networks. IEEE Communications Magazine, 2016, vol. 54, no. 8, pp. 110-117. DOI: 10.1109/MCOM.2016.7537185.

10. Zhu J., Zhao B., Lu W., Zhu Z. Attack-aware service provisioning to enhance physical-layer security in multi-domain EONs. Journal of Lightwave Technology, 2016, vol. 34, no. 11, pp. 2645-2655. DOI: 10.1109/JLT.2016.2541779.

11. Bensalem M., Brasileiro I., Drummond A., Jukan A. Embedding jamming attacks into physical layer models in optical networks. Proceedings of the International Conference on Optical Network Design and Modeling (ONDM 2020), Barcelona, Spain, 2020, pp. 1-6. DOI: 10.23919/ONDM48393.2020.9132999.

12. Ren S., Zhang Y., Wang J., Zhang J., Rao X. Research on high power intra-channel crosstalk attack in optical networks. Proceedings of SPIE. Fourth International Conference on Optical and Photonics Engineering, 2017, vol. 10250, art. 102502G. DOI: 10.1117/12.2266850.

13. Kanaev A. K., Ivanin A. N. On approaches to modeling the functioning of transport communication networks in the context of network and computer attacks based on Markov process theory. Wave Electronics and its Application in Information and Telecommunication Systems (WECONF 2020), Saint Petersburg, Russia, 2020, art. 9131431. DOI: 10.1109/WECONF48837.2020.9131431.

14. Kanaev A. K., Privalov A. A., Ivanin A. N. Simulation model of backhaul network operation under network and computer attacks. Informatsiya i Kosmos, 2020, no. 1, pp. 18-26 (In Russian).

15. Kanaev A. K., Ivanin A. N., Sokolov A. S., Shcherbak K. P. Neural network analysis of spectral contamination in the interests of ensuring the resilience of optical communication networks. Informatsiya i Kosmos, 2025, no. 4, pp. 6-11 (In Russian).

16. Rossiiskii rynok DWDM: «liambda za servis» [Russian DWDM market: "lambda as a service"]. IKS-Media. 05.02.2020. Available at: https://www.iksmedia.ru/articles/5643321-Rossijskij-rynok-DWDM-lyambda-za.html (accessed 23 August 2026) (in Russian).

17. Recommendation ITU-T G.694.1. Spectral Grids for WDM Applications: DWDM Frequency Grid. Geneva, International Telecommunication Union, 2020.

18. Agrawal G. P. Fiber-Optic Communication Systems. 5th ed. Hoboken, John Wiley & Sons, 2021. 544 p.

19. Agrawal G. P. Nonlinear Fiber Optics. 6th ed. Amsterdam, Academic Press, 2019. 728 p.

20. Meyer C. A., Floudas C. A. Trilinear monomials with positive or negative domains: facets of the convex and concave envelopes. In: Floudas C. A., Pardalos P. M. (eds.) Frontiers in Global Optimization. Boston, MA, Springer, 2003, pp. 327-352. DOI: 10.1007/978-1-4613-0251-3_18.

21. Floudas C. A., Akrotirianakis I. G., Caratzoulas S. et al. Global optimization in the 21st century: advances and challenges. Computers & Chemical Engineering, 2005, vol. 29, iss. 6, pp. 1185-1202. DOI: 10.1016/j.compchemeng.2005.02.006.

22. Tawarmalani M., Sahinidis N. V. Global optimization of mixed-integer nonlinear programs: a theoretical and computational study. Mathematical Programming, 2004, vol. 99, no. 3, pp. 563-591. DOI: 10.1007/s10107-003-0467-6.

23. Golumbic M. C. Algorithmic Graph Theory and Perfect Graphs. 2nd ed. Amsterdam, Elsevier, 2004, vol. 57.

24. Gavril F. Algorithms for minimum coloring, maximum clique, minimum covering by cliques, and maximum independent set of a chordal graph. SIAM Journal on Computing, 1972, vol. 1, no. 2, pp. 180-187. DOI: 10.1137/0201013.

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