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"DISBELIEVE: Distance Between Client Models Is Very Essential for Effective ..."

Indu Joshi et al. (2023)

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DOI: 10.1007/978-3-031-47401-9_29

access: closed

type: Conference or Workshop Paper

metadata version: 2023-12-09

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  dblp key:
  - conf/miccai/JoshiUNSN23
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  - https://dblp.org/rec/conf/miccai/JoshiUNSN23
Indu Joshi, Priyank Upadhya, Gaurav Kumar Nayak, Peter Schüffler, Nassir Navab:
DISBELIEVE: Distance Between Client Models Is Very Essential for Effective Local Model Poisoning Attacks. ISIC/Care-AI/MedAGI/DeCaF@MICCAI 2023: 297-310

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