AN APPROACH TO ENHANCING HYBRID CYBERATTACK NETWORK SURVIVABILITY DURING BLACKOUTS

Serhii Zybin, Dmytro Prokopovych-Tkachenko, Rostyslav Palahusynets, Yuliia Khokhlachova, Anton Herasymenko

Abstract


The subject of the study is the development process of SOHO (Small Office / Home Office) electronic communications networks based on a compact GPON (Gigabit-capable Passive Optical Network) mini OLT (Optical Line Terminal) with one PON (Passive Optical Network) port for up to 32 ONU/ONT (Optical Network Unit/Optical Network Terminal) subscriber terminals. This study aims to develop and validate an enhanced network survivability approach under hybrid cyberattacks during blackouts. The research tasks are as follows: a formal model of SOHO access survivability should be developed that considers the UPS energy budget and the structure of active nodes; a hybrid risk model in which energy failures are combined with cyber compromise should be formalized; the monitoring methodology IDS+SIEM (Intrusion Detection System + Security Information and Event Management) with machine learning should be developed; a comparative analysis of Ethernet and GPON architectures should be performed; practical recommendations for the implementation, diagnostics and streamlining of management should be formulated in accordance with the principles of Zero Trust and the requirements of information security management, taking into account the human factor and the ease of use of controls in SOHO. The following results were obtained. The survivability model was developed that combines the power backup circuit (UPS autonomy assessment), the availability of the active circuit, and a probabilistic model of the risk of compromising control components, including firmware attacks related to SNMP (Simple Network Management Protocol) and SSL/TLS (Secure Sockets Layer/Transport Layer Security) vulnerabilities in embedded software. A monitoring methodology that integrates IDS and SIEM with deep-learning-based analytical model classes was developed and represented by AE+LSTM-type (Autoencoder + Long Short-Term Memory) telemetry analysis and CNN+LSTM-type (Convolutional Neural Network + LSTM) firmware-oriented analysis. Comparative modeling of Ethernet Everywhere and GPON architectures with passive branching was performed for 5–20–32 connection scaling scenarios. Numerical examples of calculations, comparative tables of metrics, and the practical algorithm for diagnosing typical installation errors (APC/UPC, IN/OUT splitter, incompatibility of standards) were provided. The results were interpreted using Zero Trust principles for small networks and the prospects of multimodal AI for correlating SIEM events with firmware artifacts and physical optical channel telemetry were identified. Practical recommendations regarding segmentation, update policies, and privilege minimization for access control in the SOHO segment were offered. Conclusions. This study determines that enhancing network survivability is an important and urgent task. The scientific novelty of the results obtained is as follows: the integrated monitoring methodology with machine learning that ensure the transition from component composition and operational assumptions to numerical metrics of survivability, availability, and detection was developed; the formal survivability model was developed considering the UPS energy budget and the structure of active nodes was developed; the risk of hybrid events in which energy failures are combined with cyber compromise was formalized. Areas for further research: failure localization methodology; methodologies related to Zero Trust; multimodal AI analysis; decision support under conditions of limited SOHO resources.


Keywords


cybersecurity; SOHO; blackout; GPON; mini OLT; IDS, SIEM, Zero Trust.

References


Wan, Y., & Cao, J. A Brief Survey of Recent Advances and Methodologies for the Security Control of Complex Cyber–Physical Networks. Sensors, 2023, vol. 23, issue 8, article no. 4013. DOI: 10.3390/s23084013.

Ring, M., Wunderlich, S., Scheuring, D., Landes, D., & Hotho, A. A survey of network-based intrusion detection data sets. Computers & Security, 2019, vol. 86, pp. 147–167. DOI: 10.1016/j.cose.2019.06.005.

Cavalcanti, M. M. L., Teixeira, G. W., Dinarte, H. A., Almeida, R. C., Boutaba, R., & Chaves, D. A. R. Enhancing the Efficiency of Resilient Multipath-Routed Elastic Optical Networks: A Novel Approach for Coexisting Protected and Unprotected Services with Idle Slot Reuse. Sensors, 2024, vol. 24, issue 12, article no. 3965. DOI: 10.3390/s24123965.

Ashraf, M., Idrus, S., Iqbal, F., Butt, R., & Faheem, M. Disaster-Resilient Optical Network Survivability: A Comprehensive Survey. Photonics, 2018, vol. 5, issue 4, article no. 35. DOI: 10.3390/photonics5040035.

Shen, G., Guo, H., & Bose, S. K. Survivable elastic optical networks: survey and perspective (invited). Photonic Network Communications, 2016, vol. 31, pp. 71–87. DOI: 10.1007/s11107-015-0532-0.

Korchenko, O., Korchenko, A., Zybin, S., & Davydenko, K. An approach for classifying sociotechnical attacks. Radioelectronic and Computer Systems, 2025, vol. 2025(2), pp. 230–252. DOI: 10.32620/reks.2025.2.15.

Mushtaq, S., Mohsin, M., & Mushtaq, M. M. A Systematic Literature Review on the Implementation and Challenges of Zero Trust Architecture Across Domains. Sensors, 2025, vol. 25, issue 19, article no. 6118. DOI: 10.3390/s25196118.

Zybin, S., Khoroshko, V., Khokhlachova, Y., & Kozachok, V. Approach of the Attack Analysis to Reduce Omissions in the Risk Management. Proceedings of Selected Papers of the Workshop on Cybersecurity Providing in Information and Telecommunication Systems, 2021, vol. 2923, pp. 318–328. Available at: http://ceur-ws.org/Vol-2923/paper35.pdf (accessed February 08, 2026).

Salazar, L., Castro, S. R., Lozano, J., Koneru, K., Zambon, E., Huang, B., Baldick, R., Krotofil, M., Rojas, A., & Cardenas, A. A. A Tale of Two Industroyers: It was the Season of Darkness. 2024 IEEE Symposium on Security and Privacy, 2024, pp. 312–330. DOI: 10.1109/sp54263.2024.00162.

Durumeric, Z., Ma, Z., Springall, D., Barnes, R., Sullivan, N., Bursztein, E., Bailey, M., Halderman, J. A., & Paxson, V. The security impact of HTTPS interception. Proceedings of the 2017 Network and Distributed System Security Symposium (NDSS 2017), 2017. DOI: 10.14722/ndss.2017.23456.

Ashfaq, F., Wasim, M., Shah, M. A., Ahad, A., & Pires, I. M. Enhancing Security in 5G Edge Networks: Predicting Real-Time Zero Trust Attacks Using Machine Learning in SDN Environments. Sensors, 2025, vol. 25, issue 6, article no. 1905. DOI: 10.3390/s25061905.

Huang, J., Chen, Z., Liu, S.-Z., Zhang, H., & Long, H.-X. Improved Intrusion Detection Based on Hybrid Deep Learning Models and Federated Learning. Sensors, 2024, vol. 24, issue 12, article no. 4002. DOI: 10.3390/s24124002.

Han, D., Li, H., Fu, X., & Zhou, S. Traffic Feature Selection and Distributed Denial of Service Attack Detection in Software-Defined Networks Based on Machine Learning. Sensors, 2024, vol. 24, issue 13, article no. 4344. DOI: 10.3390/s24134344.

Oyucu, S., Polat, O., Türkoğlu, M., Polat, H., Aksöz, A., & Ağdaş, M. T. Ensemble Learning Framework for DDoS Detection in SDN-Based SCADA Systems. Sensors, 2023, vol. 24, issue 1, article no. 155. DOI: 10.3390/s24010155.

Talpur, F., Korejo, I. A., Chandio, A. A., Ghulam, A., & Talpur, M. S. H. ML-Based Detection of DDoS Attacks Using Evolutionary Algorithms Optimization. Sensors, 2024, vol. 24, issue 5, article no. 1672. DOI: 10.3390/s24051672.

Nataraj, L., Karthikeyan, S., Jacob, G., & Manjunath, B. Malware images: visualization and automatic classification. Proceedings of the 8th International Symposium on Visualization for Cyber Security (VizSec ’11), 2011, article no. 4, pp. 1–7. DOI: 10.1145/2016904.2016908.

Chatterjee, B. C., Sarma, N., & Oki, E. Routing and Spectrum Allocation in Elastic Optical Networks: A Tutorial. IEEE Communications Surveys & Tutorials, 2015, vol. 17, issue 3, pp. 1776–1800. DOI: 10.1109/comst.2015.2431731.

Chatterjee, B. C., Ba, S., & Oki, E. Fragmentation Problems and Management Approaches in Elastic Optical Networks: A Survey. IEEE Communications Surveys & Tutorials, 2018, vol. 20, issue 1, pp. 183–210. DOI: 10.1109/comst.2017.2769102.

Bao, B., Yang, H., Yao, Q., Yu, A., Chatterjee, B. C., Oki, E., & Zhang, J. SDFA: A Service-Driven Fragmentation-Aware Resource Allocation in Elastic Optical Networks. IEEE Transactions on Network and Service Management, 2022, vol. 19, issue 1, pp. 353–365. DOI: 10.1109/tnsm.2021.3116757.

Lira, C. J. N., Almeida, R. C., & Chaves, D. A. R. Spectrum allocation using multiparameter optimization in elastic optical networks. Computer Networks, 2022, vol. 220, article no. 109478. DOI: 10.1016/j.comnet.2022.109478.

Mehrabi, M., Beyranvand, H., & Emadi, M. J. Multi-Band Elastic Optical Networks: Inter-Channel Stimulated Raman Scattering-Aware Routing, Modulation Level and Spectrum Assignment. Journal of Lightwave Technology, 2021, vol. 39, issue 11, pp. 3360–3370. DOI: 10.1109/jlt.2021.3065297.

Liu, Y., Feng, N., Shen, L., Lv, J., Yan, D., & Zhao, J. Fragmentation and ISRS-Aware Survivable Routing, Band, Modulation, and Spectrum Allocation Algorithm in Multi-Band Elastic Optical Networks. Applied Sciences, 2024, vol. 14, issue 11, article no. 4755. DOI: 10.3390/app14114755.

Abuelela, E., Żal, M., & Kabaciński, W. Simultaneous Connections Routing in Wavelength–Space–Wavelength Elastic Optical Switches. Sensors, 2023, vol. 23, issue 7, article no. 3615. DOI: 10.3390/s23073615.

Rodrigues, E., Cerqueira, E., Rosário, D., & Oliveira, H. Hybrid Routing, Modulation, Spectrum and Core Allocation Based on Mapping Scheme. Sensors, 2020, vol. 20, issue 21, article no. 6393. DOI: 10.3390/s20216393.




DOI: https://doi.org/10.32620/reks.2026.2.14

Refbacks

  • There are currently no refbacks.