Differentially Private Federated Learningfor Anomaly Detection in eHealth Networks-Reference-Cited by-同舟云学术

Differentially Private Federated Learningfor Anomaly Detection in eHealth Networks

Published:2021-09-21 Issue: Volume: Page:
ISSN:
Container-title:Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers
language:
Short-container-title:

Author:

Cholakoska Ana¹,Pfitzner Bjarne²,Gjoreski Hristijan³,Rakovic Valentin¹,Arnrich Bert²,Kalendar Marija¹

Affiliation:

1. Faculty of Electrical Engineering and Information Technologies and Faculty of Electrical Engineering and Information Technologies, Macedonia, The Former Yugoslav Republic of

2. Hasso Plattner Institute and Hasso Plattner Institute, Germany

3. Ss. Cyril and Methodius University and Ss. Cyril and Methodius University, Macedonia, The Former Yugoslav Republic of

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3460418.3479365

Reference23 articles.

1. Deep Learning with Differential Privacy

2. The Algorithmic Foundations of Differential Privacy;Dwork Cynthia;Found. Trends Theor. Comput. Sci.,2014

Cited by 9 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. Recent methodological advances in federated learning for healthcare;Patterns;2024-06

2. FEDDBN-IDS: federated deep belief network-based wireless network intrusion detection system;EURASIP Journal on Information Security;2024-04-04

3. Enhancing Internet of Medical Things security with artificial intelligence: A comprehensive review;Computers in Biology and Medicine;2024-03

4. FingerFaker: Spoofing Attack on COTS Fingerprint Recognition Without Victim's Knowledge;Proceedings of the 21st ACM Conference on Embedded Networked Sensor Systems;2023-11-12

5. Privacy-preserving malware detection in Android-based IoT devices through federated Markov chains;Future Generation Computer Systems;2023-11