34 citations · 113 across the 17 of their papers we have counts for
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cs.CR2023
Leveraging Diffusion-Based Image Variations for Robust Training on Poisoned Data
Lukas Struppek, Martin B. Hentschel, Clifton Poth +2
Backdoor attacks pose a serious security threat for training neural networks as they surreptitiously introduce hidden functionalities into a model. Such backdoors remain silent dur…
cs.CR2022★ 1 cited
Combining AI and AM - Improving Approximate Matching through Transformer Networks
Frieder Uhlig, Lukas Struppek, Dominik Hintersdorf +3
Approximate matching (AM) is a concept in digital forensics to determine the similarity between digital artifacts. An important use case of AM is the reliable and efficient detecti…