Gefei Tan
@GefeiTan
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CS PhD Student @ NU Cryptography
Evanston
Joined July 2022
We explored the implication of existing proof of training and how to design ZK proof of training with realistic implications. Checkout our paper at: https://t.co/6WXsKrZlxk
eprint.iacr.org
Zero-knowledge proofs of training (zkPoT) allow a party to prove that a model is trained correctly on a committed dataset without revealing any additional information about the model or the dataset....
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Our work on privacy-preserving regular expression matching using TNFA: https://t.co/nSJDVHLuqn is accepted by ESORICS 2024. This is joint work with @CWeng15, Jaspal Singh, @GefeiTan, Ruzica Piskac, and Mariana Raykova.
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