Blockchain-Based Federated Learning with Enhanced Privacy and Security Using Homomorphic Encryption and Reputation
Federated learning, leveraging distributed data from multiple nodes to train a common
model, allows for the use of more data to improve the model while also protecting the privacy …
model, allows for the use of more data to improve the model while also protecting the privacy …
Efficiency of Federated Learning and Blockchain in Preserving Privacy and Enhancing the Performance of Credit Card Fraud Detection (CCFD) Systems
Increasing global credit card usage has elevated it to a preferred payment method for daily
transactions, underscoring its significance in global financial cybersecurity. This paper …
transactions, underscoring its significance in global financial cybersecurity. This paper …
SSCM: a secured approach to supply chain management with control management using blowfish optimization
S Selvarajan, H Manoharan, AO Khadidos… - Enterprise Information …, 2024 - Taylor & Francis
This study examines the importance of enterprise information systems that link several
corporate organisations to share information about diverse products under high security …
corporate organisations to share information about diverse products under high security …
FedSBS: Federated-Learning participant-selection method for Intrusion Detection Systems
Federated Learning (FL) is a decentralized machine learning approach in which multiple
participants collaboratively train a model. Participants keep data locally, train their local …
participants collaboratively train a model. Participants keep data locally, train their local …
Leveraging Network Data Analytics Function and Machine Learning for Data Collection, Resource Optimization, Security and Privacy in 6G Networks
The full deployment of sixth-generation (6G) networks is inextricably connected with a
holistic network redesign able to deal with various emerging challenges, such as integration …
holistic network redesign able to deal with various emerging challenges, such as integration …
Fortifying Federated Learning in IIoT: Leveraging Blockchain and Digital Twin Innovations for Enhanced Security and Resilience
SB Prathiba, Y Govindarajan, VPA Ganesan… - IEEE …, 2024 - ieeexplore.ieee.org
Ensuring robustness against adversarial attacks is imperative for Machine Learning (ML)
systems within the critical infrastructures of the Industrial Internet of Things (IIoT). This paper …
systems within the critical infrastructures of the Industrial Internet of Things (IIoT). This paper …
[HTML][HTML] Dynamic Semi-Supervised Federated Learning Fault Diagnosis Method Based on an Attention Mechanism
S Liu, F Zhou, S Tang, X Hu, C Wang, T Wang - Entropy, 2023 - mdpi.com
In cases where a client suffers from completely unlabeled data, unsupervised learning has
difficulty achieving an accurate fault diagnosis. Semi-supervised federated learning with the …
difficulty achieving an accurate fault diagnosis. Semi-supervised federated learning with the …
FedSBS: Seleçao de Participantes Baseado em Pontuaçao para Aprendizado Federado no Cenário de Detecçao de Intrusao
Sistemas de Detecção de Intrusão baseados em Aprendizado Federado apresentam
desafios para a segurança cibernética, incluindo a gestão de dados desbalanceados e …
desafios para a segurança cibernética, incluindo a gestão de dados desbalanceados e …