Federated Conditional Variational Auto Encoders for Cyber Threat Intelligence: Tackling Non-IID Data in SDN Environments

Federated Conditional Variational Auto Encoders for Cyber Threat Intelligence: Tackling Non-IID Data in SDN Environments

Federated Learning is a promising paradigm for sharing Cyber Threat Intelligence (CTI) without privacy issues by leveraging the cross-silos data in Software Defined Networking (SDN). However, with the heterogenous nature of future sixth generation (6G) systems and continuously evolving threats spect...

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Bibliographic Details
Main Authors: Syed Hussain Ali Kazmi, Rosilah Hassan, Faizan Qamar, Kashif Nisar, Mohammed Azmi Al-Betar
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Deep learning
non-IID data
6G
VAE
CTI
Online Access:https://ieeexplore.ieee.org/document/10843190/
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https://ieeexplore.ieee.org/document/10843190/

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