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FEDGAN-IDS: Privacy-preserving IDS using GAN and Federated Learning
(
Elsevier
, 2022 , Article)
Federated Learning (FL) is a promising distributed training model that aims to minimize the data sharing to enhance privacy and performance. FL requires sufficient and diverse training data to build efficient models. Lack ...
Zero Touch Realization of Pervasive Artificial Intelligence as a Service in 6G Networks
(
IEEE
, 2023 , Article)
The vision of the upcoming 6G technologies, characterized by ultra-dense networks, low latency, and fast data rate, is to support pervasive artificial intelligence (PAI) using zero touch solutions enabling self-X (e.g., ...
RL-Based Federated Learning Framework Over Blockchain (RL-FL-BC)
(
IEEE
, 2023 , Article)
Federated learning (FL) paradigms aim to amalgamate diverse data properties stored locally at each user, while preserving data privacy through sharing users’ learning experiences and iteratively aggregating their ...
Video transcoding at the edge: cost and feasibility perspective
(
Springer Nature
, 2023 , Article)
The developments in smartphones, high data rates, and substantial video data traffic have increased the burden on cellular networks. Consequently, this burden significantly affects the Quality of Experience of the cellular ...
Cross-Layer Optimal Rate Allocation for Heterogeneous Wireless Multicast
(
Hindawi Publishing Corporation
, 2009 , Article)
Heterogeneous multicast is an efficient communication scheme especially for multimedia applications running over multihop networks. The term heterogeneous refers to the phenomenon when multicast receivers in the same session ...
Ensemble Classifier for Epileptic Seizure Detection for Imperfect EEG Data
(
Hindawi
, 2015 , Article)
Brain status information is captured by physiological electroencephalogram (EEG) signals, which are extensively used to study
different brain activities.This study investigates the use of a new ensemble classifier to ...