Security of federated learning in 6G era: A review on conceptual techniques and software platforms used for research and analysis
Federated Learning (FL) is an emerging Artificial Intelligence (AI) paradigm enabling
multiple parties to train a model collaboratively without sharing their data. With the upcoming …
multiple parties to train a model collaboratively without sharing their data. With the upcoming …
Security in Federated Learning Enabled 6g Era: A Review on Conceptual Techniques and Software Platforms Used for Research and Analysis
Federated Learning (FL) is an emerging Artificial Intelligence (AI) paradigm that enables
multiple parties to collaboratively train a model without sharing their data. With the upcoming …
multiple parties to collaboratively train a model without sharing their data. With the upcoming …
A survey on security and privacy of federated learning
Federated learning (FL) is a new breed of Artificial Intelligence (AI) that builds upon
decentralized data and training that brings learning to the edge or directly on-device. FL is a …
decentralized data and training that brings learning to the edge or directly on-device. FL is a …
Secure smart communication efficiency in federated learning: Achievements and challenges
Federated learning (FL) is known to perform machine learning tasks in a distributed manner.
Over the years, this has become an emerging technology, especially with various data …
Over the years, this has become an emerging technology, especially with various data …
[HTML][HTML] Security of federated learning with IoT systems: Issues, limitations, challenges, and solutions
Abstract Federated Learning (FL, or Collaborative Learning (CL)) has surely gained a
reputation for not only building Machine Learning (ML) models that rely on distributed …
reputation for not only building Machine Learning (ML) models that rely on distributed …
Security and privacy threats to federated learning: Issues, methods, and challenges
Federated learning (FL) has nourished a promising method for data silos, which enables
multiple participants to construct a joint model collaboratively without centralizing data. The …
multiple participants to construct a joint model collaboratively without centralizing data. The …
Federated learning for cybersecurity: Concepts, challenges, and future directions
M Alazab, SP RM, M Parimala… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Federated learning (FL) is a recent development in artificial intelligence, which is typically
based on the concept of decentralized data. As cyberattacks are frequently happening in the …
based on the concept of decentralized data. As cyberattacks are frequently happening in the …
Recent advances on federated learning for cybersecurity and cybersecurity for federated learning for internet of things
Decentralized paradigm in the field of cybersecurity and machine learning (ML) for the
emerging Internet of Things (IoT) has gained a lot of attention from the government …
emerging Internet of Things (IoT) has gained a lot of attention from the government …
Fostering trustworthiness of federated learning ecosystem through realistic scenarios
The present study thoroughly evaluates the most common blocking challenges faced by the
federated learning (FL) ecosystem and analyzes existing state-of-the-art solutions. A system …
federated learning (FL) ecosystem and analyzes existing state-of-the-art solutions. A system …
[PDF][PDF] A Survey on Securing Federated Learning: Analysis of Applications, Attacks, Challenges, and Trends.
The growth of data generation capabilities, facilitated by advancements in communication
and computation technologies, as well as the rise of the Internet of Things (IoT), results in …
and computation technologies, as well as the rise of the Internet of Things (IoT), results in …