QuEST: Quantization-Conditioned Efficient Stealthy Trojan

QuEST is a new framework that makes backdoor attacks (hidden malicious behaviors injected into AI models) more stealthy and efficient when models undergo quantization (compressing models to use less memory and computation). The framework uses special training techniques and parameter sharing to hide the attack from detection systems while reducing the computational resources needed to carry out the attack.