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[HTML][HTML] Advancements in natural language processing: Implications, challenges, and future directions
This research delves into the latest advancements in Natural Language Processing (NLP)
and their broader implications, challenges, and future directions. With the ever-increasing …
and their broader implications, challenges, and future directions. With the ever-increasing …
An automated privacy-preserving self-supervised classification of COVID-19 from lung CT scan images minimizing the requirements of large data annotation
This study presents a novel privacy-preserving self-supervised (SSL) framework for COVID-
19 classification from lung CT scans, utilizing federated learning (FL) enhanced with Paillier …
19 classification from lung CT scans, utilizing federated learning (FL) enhanced with Paillier …
[HTML][HTML] FLARE: A Backdoor Attack to Federated Learning with Refined Evasion
Q Wang, Y Wu, H Xuan, H Wu - Mathematics, 2024 - mdpi.com
Federated Learning (FL) is vulnerable to backdoor attacks in which attackers inject
malicious behaviors into the global model. To counter these attacks, existing works mainly …
malicious behaviors into the global model. To counter these attacks, existing works mainly …
Blockchain Empowered Secure Federated Learning for Consumer IoT Applications in Cloud-Edge Collaborative Environment
The growing number of consumer Internet of Things (IoT) gadgets, including smart homes,
fitness trackers, connected appliances, and home security systems, is transforming the way …
fitness trackers, connected appliances, and home security systems, is transforming the way …
Research on Federated Learning Data-Sharing Mechanism Based on Communication Protocols
Y Cao, M Zhu, Y Chen - International Conference on Artificial Intelligence …, 2024 - Springer
Federated learning, as a machine learning paradigm that protects data privacy, requires
participants to collaborate in training models without sharing raw data. Therefore, an efficient …
participants to collaborate in training models without sharing raw data. Therefore, an efficient …
Research on Federated Learning Data-Sharing Mechanism Based
Y Cao, M Zhu, Y Chen - … of the Second International Conference on … - books.google.com
Federated learning, as a machine learning paradigm that protects data privacy, requires
participants to collaborate in training models without sharing raw data. Therefore, an efficient …
participants to collaborate in training models without sharing raw data. Therefore, an efficient …