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paperNovember 2025Unreviewed

Adversarial Machine Learning in Cybersecurity Attacks and Defense Mechanisms

T Chithralekha, Shivakumar E, N Legapriyadharshini

Machine Learning and Deep Learning Techniques for Cybersecurity Risk Prediction and Anomaly Detection

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Abstract

Adversarial machine learning has emerged as a critical challenge in cybersecurity, particularly with the increasing reliance on automated defense systems in modern networks. This chapter explores the evolving landscape of adversarial attacks targeting cybersecurity models, focusing on their impact on real-time threat detection and mitigation strategies. The rise of complex, multi-layered defense mechanisms in smart networks has led to more sophisticated adversarial tactics, which are designed to

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Adversarial Examples

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MITRE ATLAS
  • AML.T0043Craft Adversarial Data

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Cite

@article{chithralekha2025adversarial,
  title = {{Adversarial Machine Learning in Cybersecurity Attacks and Defense Mechanisms}},
  author = {T Chithralekha and Shivakumar E and N Legapriyadharshini},
  year = {2025},
  month = nov,
  journal = {Machine Learning and Deep Learning Techniques for Cybersecurity Risk Prediction and Anomaly Detection},
  doi = {10.71443/9789349552043-07},
  url = {https://doi.org/10.71443/9789349552043-07}
}