DARPA formulated the Explainable Artificial Intelligence (XAI) program in 2015 with the goal
to enable end users to better understand, trust, and effectively manage artificially intelligent …

Data poisoning is a threat model in which a malicious actor tampers with training data to
manipulate outcomes at inference time. A variety of defenses against this threat model have …

When machine learning training is outsourced to third parties, $ backdoor $$ attacks $
become practical as the third party who trains the model may act maliciously to inject hidden …

Recent works have demonstrated that deep learning models are vulnerable to backdoor
poisoning attacks, where these attacks instill spurious correlations to external trigger …

Trojan attacks threaten deep neural networks (DNNs) by poisoning them to behave normally
on most samples, yet to produce manipulated results for inputs attached with a particular …

This paper proposes a simple method to distill and detect backdoor patterns within an
image:\emph {Cognitive Distillation}(CD). The idea is to extract the" minimal essence" from …

Collecting training data from untrusted sources exposes machine learning services to
poisoning adversaries, who maliciously manipulate training data to degrade the model …