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Privacy Preserving Deep Learning

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A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component

21 Aug 2019

In this paper, we propose a novel privacy-preserving deep learning model and a secure training/inference scheme to protect the input, the output, and the model in the application of the neural network.

PRIVACY PRESERVING DEEP LEARNING

Private Deep Learning with Teacher Ensembles

5 Jun 2019

Privacy-preserving deep learning is crucial for deploying deep neural network based solutions, especially when the model works on data that contains sensitive information.

PRIVACY PRESERVING DEEP LEARNING

Towards Fair and Decentralized Privacy-Preserving Deep Learning with Blockchain

4 Jun 2019

DPPDL makes the first investigation on the research problem of fairness in collaborative deep learning, and simultaneously provides fairness and privacy by proposing two novel algorithms: initial benchmarking and privacy-preserving collaborative deep learning.

PRIVACY PRESERVING DEEP LEARNING

Distributed Layer-Partitioned Training for Privacy-Preserved Deep Learning

12 Apr 2019

Deep Learning techniques have achieved remarkable results in many domains.

PRIVACY PRESERVING DEEP LEARNING

Disguised-Nets: Image Disguising for Privacy-preserving Outsourced Deep Learning

5 Feb 2019

We develop an image disguising approach to address these attacks and design a suite of methods to evaluate the levels of attack resilience for a privacy-preserving solution for outsourced deep learning.

IMAGE CLASSIFICATION PRIVACY PRESERVING DEEP LEARNING

Privacy-Preserving Deep Learning via Weight Transmission

10 Sep 2018

This paper considers the scenario that multiple data owners wish to apply a machine learning method over the combined dataset of all owners to obtain the best possible learning output but do not want to share the local datasets owing to privacy concerns.

PRIVACY PRESERVING DEEP LEARNING