International Journal on Science and Technology

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Call for Paper Volume 17 Issue 3 July-September 2026 Submit your research before last 3 days of September to publish your research paper in the issue of July-September.
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Volume 17 Issue 3
July-September 2026

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AI-Enhanced Cybersecurity in Telecom Operations: Assessing Anomaly Detection, Fraud Prevention, and Network Resilience Methods

Author(s) Prashant Roy
Country India
Abstract The rapid expansion of 5G networks, IoT devices, cloud-native architectures, and massive data exchange has significantly increased cybersecurity challenges in modern telecom systems. Traditional cybersecurity approaches, which mainly rely on predefined rules and signature-based detection, are no longer sufficient to handle evolving, complex, and large-scale cyber threats. In this context, Artificial Intelligence (AI) has emerged as a powerful solution to strengthen telecom security and ensure reliable network operations. The primary objective of this study is to analyze AI-based approaches for anomaly detection, fraud prevention, and network resilience in telecom environments. The study examines key AI techniques including Machine Learning (ML), Deep Learning (DL), Reinforcement Learning (RL), behavioral analytics, and automated threat intelligence systems for identifying abnormal network behavior, detecting fraudulent activities, and enabling adaptive security responses. These techniques enhance the capability of telecom networks to detect both known and unknown attacks in real time while improving decision-making and automation in security operations. The study provides a comprehensive assessment of AI-enabled cybersecurity mechanisms and highlights their effectiveness in improving detection accuracy, reducing response time, and strengthening overall network resilience. Furthermore, it identifies major challenges such as data privacy, model interpretability, computational complexity, and adversarial attacks, along with future research directions aimed at developing intelligent, scalable, and autonomous telecom security systems.
Keywords Artificial Intelligence, Telecom Cybersecurity, Anomaly Detection, Fraud Prevention, Network Resilience, Machine Learning, Threat Intelligence
Field Computer > Network / Security
Published In Volume 17, Issue 3, July-September 2026
Published On 2026-07-26
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Crossref DOI prefix of IJSAT is 10.71097/IJSAT

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