Bridging Netops and Secops in Teclecom: Unified Monitoring and Incident Response Models

DOI

10.2991/978-94-6239-654-8_58How to use a DOI?

Keywords

NetOps-SecOps convergence; Unified monitoring; Incident response models; Blockchain-based cybersecurity; Adaptive learning algorithm; Graph intelligence; Explain AI

Abstract

This has greatly increased considerable rise in demand for integrated operative, security and safety system frameworks that are resilient against emerging immune to new forms of attacks by cyber threats with service reliability. This work proposes the paper suggest new model paradigm of bridging unification between NetOps and SecOps in telecom system environments through joint unified monitoring and incident response system mechanisms. By making use of the leveraging blockchain-based transparency capabilities of blockchain technology and an algorithm Adaptive Learning + Graph Intelligence algorithm, it has the potential to enable real-time anomaly detection, trustless event logs, and an informed decision-making process among the operatives between operational and security realms. The adaptive components of this paper learning will ensure that the process of detection continuously updates refine the detection threshold values, whereas the role of the thresholds and graph intelligence component is to express complex dependence relationships among the network entities, attack surface vectors, and response workflow processes. The proposed paradigm model has shown robust improved performance resilience, along with the improvement by reducing mean time to detect and mean time to respond, where the auditability and compliance are assured by blockchain-backed incident records. Benchmarking results and output underline significant improvements in accuracy and scalability compared to conventional siloed approaches. Looking ahead, it indicates that integrating multimodal threat intelligence, cross-domain orchestration, and ethical AI governance opens up promising vistas for the extension of this framework: embedding explainable AI for operator trust, interoperability with 5G/6G architectures, and multimodal emotion-aware SOC dashboards to enhance human operators and machines within the telecommunications of machine collaboration in the telecom cybersecurity domain.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Darshankumar Prajapati
PY  - 2026
DA  - 2026/04/24
TI  - Bridging Netops and Secops in Teclecom: Unified Monitoring and Incident Response Models
BT  - Proceedings of the Global Conference on Sustainable Energy Systems, Smart Electronics and Intelligent Computing (GCSESEIC 2025)
PB  - Atlantis Press
SP  - 734
EP  - 749
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6239-654-8_58
DO  - 10.2991/978-94-6239-654-8_58
ID  - Prajapati2026
ER  -