Data Poisoning Attacks: A Practical Guide to Label Flipping on CIFAR-10
Published:Jan 11, 2026 15:47
•1 min read
•MarkTechPost
Analysis
This article highlights a critical vulnerability in deep learning models: data poisoning. Demonstrating this attack on CIFAR-10 provides a tangible understanding of how malicious actors can manipulate training data to degrade model performance or introduce biases. Understanding and mitigating such attacks is crucial for building robust and trustworthy AI systems.
Key Takeaways
Reference
“By selectively flipping a fraction of samples from...”