Advanced artificial intelligence with federated learning framework for privacy-preserving cyberthreat detection in IoT-assisted sustainable smart cities

Advanced artificial intelligence with federated learning framework for privacy-preserving cyberthreat detection in IoT-assisted sustainable smart cities

Abstract With the fast growth of artificial intelligence (AI) and a novel generation of network technology, the Internet of Things (IoT) has become global. Malicious agents regularly utilize novel technical vulnerabilities to use IoT networks in essential industries, the military, defence systems, a...

Full description

Saved in:
Bibliographic Details
Main Authors: Mahmoud Ragab, Ehab Bahaudien Ashary, Bandar M. Alghamdi, Rania Aboalela, Naif Alsaadi, Louai A. Maghrabi, Khalid H. Allehaibi
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:Scientific Reports
Subjects:
Federated Learning
Privacy preserving
Artificial Intelligence
Cyberthreat
Smart cities
IoT
Online Access:https://doi.org/10.1038/s41598-025-88843-2
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-025-88843-2

Similar Items