1 citations · 1 across the 5 of their papers we have counts for
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A Novel Latent-Class Attack and its Detection by Class Subspace Orthogonalization
Guangmingmei Yang, David J. Miller, George Kesidis
Deep learning, which in general relies on voluminous amounts of training data, is vulnerable to data poisoning attacks, including error-generic attacks and backdoors (Trojans). In…
Improving the Sensitivity of Backdoor Detectors via Class Subspace Orthogonalization
Guangmingmei Yang, David J. Miller, George Kesidis
Most post-training backdoor detection methods rely on attacked models exhibiting extreme outlier detection statistics for the target class of an attack, compared to non-target clas…
Inverting Trojans in LLMs
Zhengxing Li, Guangmingmei Yang, Jayaram Raghuram +2
While effective backdoor detection and inversion schemes have been developed for AIs used e.g. for images, there are challenges in "porting" these methods to LLMs. First, the LLM i…