Design of an Integrated Modern Approach to Detect and Prevent Data Poisoning Attacks in AI Systems: A Multi-Stage Defense Framework for Robust and Secure Learning
Adversarial threats like data poisoning attacks affect the training datasets and create biased, worse, or malicious AI models. Static heuristics and high false positive rates have impeded traditional defenses against such adaptive stealthy attacks. These defenses also do not generalize well in federated and non-IID set...