Backdoor Attacks on Bayesian Neural Networks using Reverse Distribution. (arXiv:2205.09167v1 [cs.CR])

Due to cost and time-to-market constraints, many industries outsource the
training process of machine learning models (ML) to third-party cloud service
providers, popularly known as ML-asa-Service (MLaaS). MLaaS creates opportunity
for an adversary to provide users with backdoored ML models to produce
incorrect predictions only in extremely rare (attacker-chosen) scenarios.
Bayesian neural networks (BNN) are inherently immune against backdoor attacks
since the weights are designed to be marginal distributions to quantify the
uncertainty. In this paper, we propose a novel …

attacks backdoor distribution networks reverse