A privacy preserving framework for federated learning in smart healthcare systems
W Wang, X Li, X Qiu, X Zhang, V Brusic… - Information Processing & …, 2023 - Elsevier
Federated Learning (FL) is a platform for smart healthcare systems that use wearables and
other Internet of Things enabled devices. However, source inference attacks (SIAs) can infer …
other Internet of Things enabled devices. However, source inference attacks (SIAs) can infer …
Towards federated learning: An overview of methods and applications
Federated learning (FL) is a collaborative, decentralized privacy‐preserving method to
attach the challenges of storing data and data privacy. Artificial intelligence, machine …
attach the challenges of storing data and data privacy. Artificial intelligence, machine …
On the feasibility of federated learning towards on-demand client deployment at the edge
Nowadays, researchers are investing their time and devoting their efforts in developing and
motivating the 6G vision and resources that are not available in 5G. Edge computing and …
motivating the 6G vision and resources that are not available in 5G. Edge computing and …
Intrusion Detection based on Federated Learning: a systematic review
JL Hernandez-Ramos, G Karopoulos… - arXiv preprint arXiv …, 2023 - arxiv.org
The evolution of cybersecurity is undoubtedly associated and intertwined with the
development and improvement of artificial intelligence (AI). As a key tool for realizing more …
development and improvement of artificial intelligence (AI). As a key tool for realizing more …
Vision transformer attention with multi-reservoir echo state network for anomaly recognition
Anomalous event recognition requires an instant response to reduce the loss of human life
and property; however, existing automated systems show limited performance due to …
and property; however, existing automated systems show limited performance due to …
Prime: privacy-preserving video anomaly detection via motion exemplar guidance
Y Su, H Zhu, Y Tan, S An, M Xing - Knowledge-Based Systems, 2023 - Elsevier
Video anomaly detection (VAD) involves identifying events or behaviours in video
sequences that deviate from expected patterns. Most VAD models to date focus on seeking …
sequences that deviate from expected patterns. Most VAD models to date focus on seeking …
BFLS: Blockchain and Federated Learning for sharing threat detection models as Cyber Threat Intelligence
T Jiang, G Shen, C Guo, Y Cui, B Xie - Computer Networks, 2023 - Elsevier
Abstract Recently, Cyber Threat Intelligence (CTI) sharing has become an important weapon
for cyber defenders to mitigate the increasing number of cyber attacks in a proactive and …
for cyber defenders to mitigate the increasing number of cyber attacks in a proactive and …
[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 …
Federated reinforcement learning approach for detecting uncertain deceptive target using autonomous dual UAV system
This paper develops a cooperative federated reinforcement learning (RL) strategy that
enables two unmanned aerial vehicles (UAVs) to cooperate in learning and predicting the …
enables two unmanned aerial vehicles (UAVs) to cooperate in learning and predicting the …
Federated learning-assisted distributed intrusion detection using mesh satellite nets for autonomous vehicle protection
M Al-Hawawreh, MS Hossain - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The widespread use of intelligent consumer electronics, specifically autonomous vehicles,
has exponentially increased. The key enablers of this pervasive are the Internet of Things …
has exponentially increased. The key enablers of this pervasive are the Internet of Things …