A Trust-By-Learning Framework for Secure 6G Wireless Networks Under Native Generative AI Attacks

A Trust-By-Learning Framework for Secure 6G Wireless Networks Under Native Generative AI Attacks

Sixth-generation <inline-formula> <tex-math notation="LaTeX">$(6G)$ </tex-math></inline-formula> wireless networks will become vulnerable due to native generative AI (GenAI)-driven intelligent poisoning attacks in both the radio unit and the core network. In particu...

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Bibliographic Details
Main Authors: Md Shirajum Munir, Sravanthi Proddatoori, Manjushree Muralidhara, Trinidad Mario Dena, Walid Saad, Zhu Han, Sachin Shetty
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Open Journal of the Communications Society
Subjects:
Generative AI
6G
intelligent attacks
evidence theory
trustworthy AI
metareinforcement learning
Online Access:https://ieeexplore.ieee.org/document/11089495/
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https://ieeexplore.ieee.org/document/11089495/

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