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Using image conversion techniques to detect adversarial examples in machine learning models for tabular data
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AI
DOI：10.1016/j.asoc.2025.113288.png)
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Abstract
En 中文
• Employed unsupervised and supervised approaches for detecting adversarial examples. • Focused on machine learning models trained on tabular data. • Converted tabular data to images, leveraging the processing capabilities of deep learning techniques. • Leveraged explainability and transfer learning to enhance adversarial detection. • Achieved a detection rate of almost 100% on most of the examined datasets.
Keywords:
Security
Adversarial detection
Tabular data
Transfer learning
Image conversion
Journal
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6.6
Papers:
1.4W
Citations:
4.8W
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Cited Papers
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