When Deep Learning Meets Steganography: Protecting Inference Privacy in the Dark-Reference-Cited by-同舟云学术

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When Deep Learning Meets Steganography: Protecting Inference Privacy in the Dark

Published:2022-05-02 Issue: Volume: Page:
ISSN:
Container-title:IEEE INFOCOM 2022 - IEEE Conference on Computer Communications
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Author:

Liu Qin¹,Yang Jiamin¹,Jiang Hongbo¹,Wu Jie²,Peng Tao³,Wang Tian⁴,Wang Guojun³

Affiliation:

1. Hunan University,College of Computer Science and Electronic Engineering,P. R. China

2. Temple University,Department of Computer and Information Sciences,Philadelphia,USA

3. Guangzhou University,School of Computer Science and Cyber Engineering,P. R. China

4. Beijing Normal University & UIC,Institute of Artificial Intelligence and Future Networks,P. R. China

Funder

CERN

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9796607/9796652/09796975.pdf?arnumber=9796975

Reference58 articles.

1. Hiding Images within Images

2. Hiding data in images by simple LSB substitution

3. How to generate and exchange secrets

4. Fully homomorphic encryption using ideal lattices

5. DarKnight: A Data Privacy Scheme for Training and Inference of Deep Neural Networks;hashemi,2020

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2. A Survey on Deep Learning in Edge-Cloud Collaboration: Model Partitioning, Privacy Preservation, and Prospects;2024

3. Open Set Video HOI detection from Action-centric Chain-of-Look Prompting;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

4. Randomly-based Stepwise Multi-Level Distributed Medical Image Steganography;Engineering, Technology & Applied Science Research;2023-06-02

5. Protecting Inference Privacy With Accuracy Improvement in Mobile-Cloud Deep Learning;IEEE Transactions on Mobile Computing;2023

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