Federated learning review: Fundamentals, enabling technologies, and future applications

S Banabilah, M Aloqaily, E Alsayed, N Malik… - Information processing & …, 2022‏ - Elsevier
Federated Learning (FL) has been foundational in improving the performance of a wide
range of applications since it was first introduced by Google. Some of the most prominent …

Recent advances on federated learning for cybersecurity and cybersecurity for federated learning for internet of things

B Ghimire, DB Rawat - IEEE Internet of Things Journal, 2022‏ - ieeexplore.ieee.org
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 …

Federated learning: A survey on enabling technologies, protocols, and applications

M Aledhari, R Razzak, RM Parizi, F Saeed - IEEE Access, 2020‏ - ieeexplore.ieee.org
This paper provides a comprehensive study of Federated Learning (FL) with an emphasis
on enabling software and hardware platforms, protocols, real-life applications and use …

Federated learning for vehicular internet of things: Recent advances and open issues

Z Du, C Wu, T Yoshinaga, KLA Yau… - IEEE Open Journal of …, 2020‏ - ieeexplore.ieee.org
Federated learning (FL) is a distributed machine learning approach that can achieve the
purpose of collaborative learning from a large amount of data that belong to different parties …

Adversarial examples: A survey of attacks and defenses in deep learning-enabled cybersecurity systems

M Macas, C Wu, W Fuertes - Expert Systems with Applications, 2024‏ - Elsevier
Over the last few years, the adoption of machine learning in a wide range of domains has
been remarkable. Deep learning, in particular, has been extensively used to drive …

Blockchain for 5G and beyond networks: A state of the art survey

DC Nguyen, PN Pathirana, M Ding… - Journal of Network and …, 2020‏ - Elsevier
The fifth generation (5G) wireless networks are on the way to be deployed around the world.
The 5G technologies target to support diverse vertical applications by connecting …

Resilient machine learning for networked cyber physical systems: A survey for machine learning security to securing machine learning for CPS

FO Olowononi, DB Rawat, C Liu - … Communications Surveys & …, 2020‏ - ieeexplore.ieee.org
Cyber Physical Systems (CPS) are characterized by their ability to integrate the physical and
information or cyber worlds. Their deployment in critical infrastructure have demonstrated a …

A systematic literature review on federated machine learning: From a software engineering perspective

SK Lo, Q Lu, C Wang, HY Paik, L Zhu - ACM Computing Surveys (CSUR …, 2021‏ - dl.acm.org
Federated learning is an emerging machine learning paradigm where clients train models
locally and formulate a global model based on the local model updates. To identify the state …

When machine learning meets privacy in 6G: A survey

Y Sun, J Liu, J Wang, Y Cao… - … Surveys & Tutorials, 2020‏ - ieeexplore.ieee.org
The rapid-develo** Artificial Intelligence (AI) technology, fast-growing network traffic, and
emerging intelligent applications (eg, autonomous driving, virtual reality, etc.) urgently …

[HTML][HTML] Federated learning and its role in the privacy preservation of IoT devices

T Alam, R Gupta - Future Internet, 2022‏ - mdpi.com
Federated learning (FL) is a cutting-edge artificial intelligence approach. It is a decentralized
problem-solving technique that allows users to train using massive data. Unprocessed …