Verifiable Deep Learning Inference on Heterogeneous Edge Devices With Trusted Execution Environment-Reference-Cited by-同舟云学术

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Verifiable Deep Learning Inference on Heterogeneous Edge Devices With Trusted Execution Environment

Published:2024-09-01 Issue:17 Volume:24 Page:28351-28362
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Liao Longlong¹^ORCID,Zheng Yuqiang¹^ORCID,Lu Hong²^ORCID,Liu Xinqi³,Chen Shuguang⁴^ORCID,Yu Yuanlong¹^ORCID

Affiliation:

1. College of Computer and Data Science, Fuzhou University, Fuzhou, China

2. School of Mathematics and Information Science, Nanjing Normal University of Special Education, Nanjing, China

3. Faculty of Engineering, The University of Hong Kong, Hong Kong, China

4. Faculty of Science, The University of Hong Kong, Hong Kong, China

Funder

Natural Science Foundation of Fujian Province of China

National Natural Science Foundation of China

Qing Lan Project of Jiangsu Province

Hong Kong Quantum AI Lab, AIR@InnoHK of the Hong Kong Government

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/7361/10660640/10601614.pdf?arnumber=10601614

Reference39 articles.

1. Towards edge computing in intelligent manufacturing: Past, present and future

2. Vehicular Edge Based Approach for Optimizing Urban Data Privacy

3. Online Distributed Learning-Based Load-Aware Heterogeneous Vehicular Edge Computing

4. Human Action Recognition of Autonomous Mobile Robot Using Edge-AI

5. Fault Attacks on Secure Embedded Software: Threats, Design, and Evaluation

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