Towards privacy preserving AI based composition framework in edge networks using fully homomorphic encryption-Reference-Cited by-同舟云学术

Towards privacy preserving AI based composition framework in edge networks using fully homomorphic encryption

Published:2020-09 Issue: Volume:94 Page:103737
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Rahman Mohammad Saidur,Khalil Ibrahim,Atiquzzaman Mohammed,Yi Xun

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference43 articles.

1. Workflow-net based service composition using mobile edge nodes;Al Ridhawi;IEEE Access,2017

2. Real-time secure health surveillance for smarter health communities;Alabdulatif;IEEE Commun. Mag.,2019

3. Privacy-preserving anomaly detection in the cloud for quality assured decision-making in smart cities;Alabdulatif;J. Parallel Distrib. Comput.,2018

4. Privacy-preserving anomaly detection in the cloud for quality assured decision-making in smart cities;Alabdulatif;J. Parallel Distrib. Comput.,2019

5. Privacy-preserving data clustering in cloud computing based on fully homomorphic encryption;Alabdulatif,2017

Cited by 33 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Dynamic Defense Strategies With Generative AI;Advances in Digital Crime, Forensics, and Cyber Terrorism;2024-09-13

2. Efficient Twiddle Factor Generators for NTT;Electronics;2024-08-07

3. Game-theoretic analytics for privacy preservation in Internet of Things networks: A survey;Engineering Applications of Artificial Intelligence;2024-07

4. A lightweight practical consensus mechanism for supply chain blockchain;High-Confidence Computing;2024-06

5. A Hybrid Cryptographic Mechanism for Secure Data Transmission in Edge AI Networks;International Journal of Computational Intelligence Systems;2024-02-06