pvCNN: Privacy-Preserving and Verifiable Convolutional Neural Network
Testing

pvCNN: Privacy-Preserving and Verifiable Convolutional Neural Network Testing

23 January 2022

Papers citing "pvCNN: Privacy-Preserving and Verifiable Convolutional Neural Network Testing"

10 / 10 papers shown

Title
ExpProof : Operationalizing Explanations for Confidential Models with ZKPs Chhavi Yadav Evan Monroe Laufer Dan Boneh Kamalika Chaudhuri 118 0 0 06 Feb 2025
Privacy-Preserving Model and Preprocessing Verification for Machine Learning Wenbiao Li Anisa Halimi Xiaoqian Jiang Jaideep Vaidya Erman Ayday AAML 83 0 0 14 Jan 2025
Testing Framework for Black-box AI Models Aniya Aggarwal Samiullah Shaikh Sandeep Hans Swastik Haldar Rema Ananthanarayanan Diptikalyan Saha 26 8 0 11 Feb 2021
CrypTFlow: Secure TensorFlow Inference Nishant Kumar Mayank Rathee Nishanth Chandran Divya Gupta Aseem Rastogi Rahul Sharma 128 242 0 16 Sep 2019
Partially Encrypted Machine Learning using Functional Encryption T. Ryffel Edouard Dufour Sans Romain Gay Francis R. Bach D. Pointcheval FedML 33 33 0 24 May 2019
Cache Telepathy: Leveraging Shared Resource Attacks to Learn DNN Architectures Mengjia Yan Christopher W. Fletcher Josep Torrellas MIACV FedML 59 247 0 14 Aug 2018
DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems Lei Ma Felix Juefei Xu Fuyuan Zhang Jiyuan Sun Minhui Xue ... Ting Su Li Li Yang Liu Jianjun Zhao Yadong Wang ELM 65 620 0 20 Mar 2018
Gazelle: A Low Latency Framework for Secure Neural Network Inference Chiraag Juvekar Vinod Vaikuntanathan A. Chandrakasan 46 889 0 16 Jan 2018
Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning Xinyun Chen Chang-rui Liu Yue Liu Kimberly Lu D. Song AAML SILM 95 1,832 0 15 Dec 2017
Time-Optimal Interactive Proofs for Circuit Evaluation J. Thaler 69 222 0 13 Apr 2013

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