Neural Network Trojans Analysis and Mitigation from the Input Domain. (arXiv:2202.06382v2 [cs.LG] UPDATED)

Deep Neural Networks (DNNs) can learn Trojans (or backdoors) from benign or
poisoned data, which raises security concerns of using them. By exploiting such
Trojans, the adversary can add a fixed input space perturbation to any given
input to mislead the model predicting certain outputs (i.e., target labels). In
this paper, we analyze such input space Trojans in DNNs, and propose a theory
to explain the relationship of a model's decision regions and Trojans: a
complete and accurate Trojan corresponds …

analysis domain input lg mitigation network neural network trojans