Silent Killer: Optimizing Backdoor Trigger Yields a Stealthy and Powerful Data Poisoning Attack. (arXiv:2301.02615v1 [cs.CR])

We propose a stealthy and powerful backdoor attack on neural networks based
on data poisoning (DP). In contrast to previous attacks, both the poison and
the trigger in our method are stealthy. We are able to change the model's
classification of samples from a source class to a target class chosen by the
attacker. We do so by using a small number of poisoned training samples with
nearly imperceptible perturbations, without changing their labels. At inference
time, we use a …

attack attacks backdoor change class classification data data poisoning killer networks neural networks poisoning silent target training trigger