AI-Driven Security Architecture for 5G and Next-Generation Telecom Networks

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@article{1723751,
      author = {Karthick Cherladine},
      title = {AI-Driven Security Architecture for 5G and Next-Generation Telecom Networks},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {6},
      number = {7},
      pages = {612-617},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1723751.pdf},
      abstract = {The rapid deployment of 5G and emerging next-generation telecom networks introduces complex security challenges due to massive connectivity, network slicing, edge computing, IoT integration, and sophisticated cyberattacks. This project proposes an AI-driven security architecture that integrates machine learning, anomaly detection, threat classification, and automated response mechanisms to strengthen network protection. The proposed architecture analyzes network traffic and identifies abnormal patterns associated with attacks such as intrusion, denial-of-service, malware, and unauthorized access. By combining intelligent detection with real-time security monitoring, the framework aims to improve detection accuracy, reduce response time, and provide adaptive protection for reliable and secure next-generation telecommunications networks.},
      keywords = {Artificial Intelligence, 5G Networks, Next-Generation Telecom Networks, Cybersecurity, Machine Learning, Intrusion Detection, Anomaly Detection, Network Security.},
      month = {January},
      doi = {https://doi.org/10.64388/IREV6I7-1723751}
  }