Joint Knowledge Distillation and Local Differential Privacy for Communication-Efficient Federated Learning in Heterogeneous Systems

Author:

Gad Gad1,Fadlullah Zubair Md1,Fouda Mostafa M.2,Ibrahem Mohamed I.3,Nasser Nidal4

Affiliation:

1. Western University,Department of Computer Science,London,ON,Canada

2. Idaho State University,Department of Electrical and Computer Engineering,Pocatello,ID,USA

3. School of Computer and Cyber Sciences, Augusta University,Augusta,GA,USA

4. College of Engineering, Alfaisal University,Saudi Arabia

Publisher

IEEE

Cited by 4 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. A Robust Federated Learning Approach for Combating Attacks Against IoT Systems Under Non-IID Challenges;2024 International Conference on Smart Applications, Communications and Networking (SmartNets);2024-05-28

2. Combating Malware Traffic in Emerging Networks: A Collaborative Learning Approach;2024 International Conference on Smart Applications, Communications and Networking (SmartNets);2024-05-28

3. Protecting Privacy in IoMT-based Disease Diagnosis Using an Efficient Approach;2024 IEEE 3rd International Conference on Computing and Machine Intelligence (ICMI);2024-04-13

4. Enhancing Anomaly Detection of IoT using Knowledge-Based and Federated Deep Learning;2024 IEEE 3rd International Conference on Computing and Machine Intelligence (ICMI);2024-04-13

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