Open Access

Next-Generation Security Operations Centers: A Holistic Framework Integrating Artificial Intelligence, Federated Learning, and Sustainable Green Infrastructure for Proactive Threat Mitigation

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Dr. Lukas Reinhardt ¹ ,

⁴ Independent Researcher, Distributed AI, Privacy-Preserving Systems & Green IT, Munich, Germany

Abstract

Background: The exponential growth of cyber threats, particularly ransomware and Advanced Persistent Threats (APTs), has rendered traditional, reactive Security Operations Centers (SOCs) insufficient. As attack vectors diversify across social media, industrial control systems (ICS), and cloud environments, the volume of security telemetry exceeds human cognitive capacity.

Methods: This study synthesizes recent advancements in Artificial Intelligence (AI), Federated Learning, and Green Infrastructure to propose a "Cognitive-Green SOC" framework. We analyze a corpus of distinct studies, evaluating architectures ranging from Transformer-based threat identification to blockchain-enabled federated forests. The methodology integrates an AI-optimized playbook for ransomware investigation with dynamic workload optimization strategies to reduce the carbon footprint of intensive cryptographic computations.

Results: The analysis demonstrates that integrating End-to-End architectures like RANK and Transformer models significantly improves detection rates for persistent attacks and social media threats compared to traditional heuristics. Furthermore, the integration of Green Infrastructure principles optimizes chip design and network loads, mitigating the high energy costs associated with continuous ML training.

Conclusion: The transition to Next-Gen SOCs requires more than just algorithmic upgrades; it demands a holistic architectural shift. By embedding explainable anomaly detection and prioritizing sustainable computing, organizations can achieve robust security postures that are both operationally efficient and environmentally responsible.

Keywords

Next-Gen SOC, Artificial Intelligence, Ransomware Investigation, Federated Learning

References

Prassanna R Rajgopal. (2025). AI-optimized SOC playbook for Ransomware Investigation. International Journal of Data Science and Machine Learning, 5(02), 41-55. https://doi.org/10.55640/ijdsml-05-02-04

Aliyu, I., Van Engelenburg, S., Mu’Azu, M. B., Kim, J., & Lim, C. G. (2022). Statistical detection of adversarial examples in blockchain-based federated forest in-vehicle network intrusion detection systems. IEEE Access, 10, 109366–

Gao, Y., Kim, Y., Doan, B. G., Zhang, Z., Zhang,

G., Nepal, S., Ranasinghe, D. C., & Kim, H. (2022). Design and evaluation of a multi-domain trojan detection method on deep neural networks. IEEE Trans. Depend. Secure Comput., 19(4), 2349–

Gu, K., Dong, X., Li, X., & Jia, W. (2022). Cluster- based malicious node detection for false downstream data in fog computing-based VANETs. IEEE Trans. Netw. Sci. Eng., 9(3), 1245–1263.

Huong, T. T., Bac, T. P., Ha, K. N., Hoang, N. V.,

Hoang, N. X., Hung, N. T., & Tran, K. P. (2022).

Federated learning-based explainable anomaly detection for industrial control systems. IEEE Access, 10, 53854–53872.

Kumbale, S., Singh, S., Poornalatha, G., & Singh,

S. (2023). BREE-HD: A transformer-based model to identify threats on Twitter. IEEE Access, 11, 67180–67190.

Perera, A., Rathnayaka, S., Perera, N. D., Madushanka, W.W., & Senarathne, A.N. (2021). The next-gen security operation center. 2021 6th International Conference for Convergence in Technology (I2CT), Maharashtra, India, 2021, 1-9.

Prasad, S. (2021). Cyber security operations center ML framework for the needs of the users. International Journal of Machine Learning for Sustainable Development, 3(3), 11-20.

Robert Seamans and Manav Raj. (2018). Ai, labor, productivity and the need for firm-level data. NBER Working Papers, 24239:1–34.

RSI (2021, September 16). NIST security operations center best practices. Retrieved February 21, 2023.

Sathana, M., & Hemamalini, M. (2022). A thread based machine learning framework for cyber security operations center. International Journal of Research Publication and Reviews, 3(5), 3683-

Shutock, M., & Dietrich, G. (2022). Security Operations Centers: A holistic view on problems

and solutions. Proceedings of the 55th Hawaii International Conference on System Sciences. 7555-7563.

Soliman, H. M., Sovilj, D., Salmon, G., Rao, M., & Mayya, N. (2024). RANK: AI-assisted end-to-end architecture for detecting persistent attacks in enterprise networks. IEEE Trans. Depend. Secure Comput., 21(4), 3834–3850.

Splunk (n.d.). 10 Essential capabilities of a modern SOC. E-Book, Retrieved September 19, 2023.

Trellix (n.d.). What is Endpoint Detection and Response (EDR)? Retrieved February 6, 2023.

Vemulapalli, G., & Pulivarthy, P. (2025). Integrating Green Infrastructure With AI-Driven Dynamic Workload Optimization: Focus on Network and Chip Design. In Integrating Blue- Green Infrastructure Into Urban Development, IGI Global, USA, pp. 397-422.

Vielberth, M., Böhm, F., Fichtinger, I., & Pernul,

G. (2020). Security operations center: A systematic study and open challenges. IEEE Access, 8, 227756–227779.

Yeshwanth, M. V., Kalluri, R., Rao, M. S., Kumar,

R. K. S., & Bindhumadhava, B. S. (2022). Adoption and assessment of machine learning algorithms in security operations center for critical infrastructure. In: Pillai, R.K., Ghatikar, G., Sonavane, V.L., Singh, B.P. (eds) ISUW 2020. Lecture Notes in Electrical Engineering, 847. Springer, Singapore.

Yeverechyahu, D., Mayya, R., & Oestreicher- Singer, G. (2024). The impact of large language models on open-source innovation: Evidence from Github Copilot. arXiv preprint arXiv: 2409.08379.

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International Journal of Advanced Artificial Intelligence Research

Next-Generation Security Operations Centers: A Holistic Framework Integrating Artificial Intelligence, Federated Learning, and Sustainable Green Infrastructure for Proactive Threat Mitigation

Abstract

Keywords

References

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