VeriDP: Verifiable Differentially Private Training
VeriDP is presented, a framework for verifiable differentially private training that cryptographically enforces and proves the correct execution of differentially private stochastic gradient descent (DP-SGD) in zero knowledge, uniting differential privacy and verifiable computation for secure and auditable ML.