VeriML: Enabling Integrity Assurances and Fair Payments for Machine
Learning as a Service

VeriML: Enabling Integrity Assurances and Fair Payments for Machine Learning as a Service

16 September 2019

Qi Li

Chao Shen

Papers citing "VeriML: Enabling Integrity Assurances and Fair Payments for Machine Learning as a Service"

10 / 10 papers shown

Title
VeriSplit: Secure and Practical Offloading of Machine Learning Inferences across IoT Devices Han Zhang Zifan Wang Mihir Dhamankar Matt Fredrikson Yuvraj Agarwal 75 2 0 02 Jun 2024
Verifiable and Provably Secure Machine Unlearning Thorsten Eisenhofer Doreen Riepel Varun Chandrasekaran Esha Ghosh O. Ohrimenko Nicolas Papernot AAML MU 67 26 0 17 Oct 2022
A Domain Adaptive Density Clustering Algorithm for Data with Varying Density Distribution Jianguo Chen Philip S. Yu 34 54 0 23 Nov 2019
Augmenting Encrypted Search: A Decentralized Service Realization with Enforced Execution Shengshan Hu Chengjun Cai Qian Wang Cong Wang Minghui Li Peng Kuang Dengpan Ye 30 20 0 20 Sep 2019
A scalable verification solution for blockchains Jason Teutsch Christian Reitwießner 42 216 0 12 Aug 2019
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware Florian Tramèr Dan Boneh FedML 168 396 0 08 Jun 2018
A Zero Knowledge Sumcheck and its Applications A. Chiesa Michael A. Forbes Nicholas Spooner 33 54 0 07 Apr 2017
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 228 4,103 0 18 Oct 2016
Stealing Machine Learning Models via Prediction APIs Florian Tramèr Fan Zhang Ari Juels Michael K. Reiter Thomas Ristenpart SILM MLAU 102 1,803 0 09 Sep 2016
Time-Optimal Interactive Proofs for Circuit Evaluation J. Thaler 77 222 0 13 Apr 2013