Feb. 5, 2024, 2:12 a.m. |

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ePrint Report: Zero-Knowledge Proofs of Training for Deep Neural Networks

Kasra Abbaszadeh, Christodoulos Pappas, Dimitrios Papadopoulos, Jonathan Katz


A zero-knowledge proof of training (zkPoT) enables a party to prove that they have correctly trained a committed model based on a committed dataset without revealing any additional information about the model or the dataset. An ideal zkPoT should offer provable security and privacy guarantees, succinct proof size and verifier runtime, and practical prover efficiency. In this work, we present Kaizen, a …

dataset eprint report information knowledge networks neural networks party proof prove report training

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