ARTIFICIAL INTELLIGENCE APPLICATIONS IN TELECOMMUNICATIONS CYBERSECURITY AND THREAT DETECTION SYSTEMS

Аннотация

Artificial intelligence has become an increasingly important component of telecommunications cybersecurity as network complexity, traffic volume, and cyber threats continue to expand. This study examines the applications of artificial intelligence in threat detection, anomaly identification, malware analysis, intrusion detection, and automated incident response within telecommunications environments. A qualitative research methodology based on structured literature review, comparative analysis, and conceptual evaluation was employed. The findings indicate that machine learning, deep learning, behavioral analytics, and automated classification can improve the speed and accuracy of cyber threat detection while reducing dependence on static signature-based mechanisms. However, challenges related to data quality, false positives, adversarial manipulation, explainability, privacy, and operational integration remain significant. The study concludes that artificial intelligence should complement rather than replace traditional cybersecurity controls and human expertise, with future systems emphasizing adaptive, transparent, privacy-conscious, and resilient threat detection architectures.