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paperApril 2026Unreviewed

Enhancing Network Security through AI-Powered Anomaly Detection Using Generative Adversarial Networks

C. Satya Kumar, Asha Sunki, Vinith Koppera, Manish Hakeem

Emerging Trends in Machine Learning, Data Science, and Internet of Things

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Abstract

Developments in communication technology have facilitated more data sharing in geographically dispersed settings, but they have also enlarged the attack surface, raising questions about network security. Research focuses on AI-based anomaly detection systems to improve Network Intrusion Detection Systems (NIDSs) in order to address this. However, data imbalance makes it more difficult for AI models to learn and effectively identify threats when legitimate traffic outnumbers malicious traffic. To

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Monitoring & Detection

Cite

@article{kumar2026enhancing,
  title = {{Enhancing Network Security through AI-Powered Anomaly Detection Using Generative Adversarial Networks}},
  author = {C. Satya Kumar and Asha Sunki and Vinith Koppera and Manish Hakeem},
  year = {2026},
  month = apr,
  journal = {Emerging Trends in Machine Learning, Data Science, and Internet of Things},
  doi = {10.2174/9798898814717126010016},
  url = {https://doi.org/10.2174/9798898814717126010016}
}