A differential privacy‐preserving deep learning caching framework for heterogeneous communication network systems-Reference-Cited by-同舟云学术

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A differential privacy‐preserving deep learning caching framework for heterogeneous communication network systems

Published:2022-08-26 Issue:12 Volume:37 Page:11142-11166
ISSN:0884-8173
Container-title:International Journal of Intelligent Systems
language:en
Short-container-title:Int J of Intelligent Sys

Author:

Wang Huanhuan¹²,Zhang Xiao¹,Xia Youbing¹,Wu Xiang¹^ORCID

Affiliation:

1. Institute of Medical Information Security Xuzhou Medical University Xuzhou China

2. School of Information and Control Engineering China University of Mining and Technology Xuzhou China

Funder

National Natural Science Foundation of China

Qinglan Project of Jiangsu Province of China

Publisher

Hindawi Limited

Subject

Artificial Intelligence,Human-Computer Interaction,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/int.23036

Reference72 articles.

1. JiangN JieW LiJ LiuX JinD.GATrust: a multi‐aspect graph attention network model for trust assessment in OSNs.IEEE Trans Knowl Data Eng.2022.doi:10.1109/TKDE.2022.3174044

2. Analysis and Optimization of Random Caching in mmWave Heterogeneous Networks

3. Observer-Based PID Security Control for Discrete Time-Delay Systems Under Cyber-Attacks

4. Resource Allocation in IoT Edge Computing via Concurrent Federated Reinforcement Learning

5. NPMML: a framework for non‐interactive privacy‐preserving multi‐party machine learning;Li T;IEEE Trans Depend Secure,2021

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1. Full Differential Privacy Preserving for Switched LPV Systems;IEEE Transactions on Systems, Man, and Cybernetics: Systems;2024-05

2. Research on differential privacy protection method based on user tendency;PLOS ONE;2023-10-26

3. An intelligent blockchain-based access control framework with federated learning for genome-wide association studies;Computer Standards & Interfaces;2023-03

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