ShalDeepDP: A Survey and Comparison of Data Poisoning in Statistical, Classical Deep Learning and Foundation Models
Advances in real-world adversarial threats have heightened concerns over the privacy and security of AI systems. One key threat is Data Poisoning, where malicious data is injected into training sets or model inputs to compromise model behavior. While much of the current research focuses on deep learning, particularly F...
Jia Yi Chan, Huaqun Guo, Timothy Liu et al.
· Singapore Institute of Techn... · 0 citations