# Security, Trust and Privacy challenges in AI-driven 6G Networks

arXiv: https://arxiv.org/abs/2409.10337 · HTML: https://mlsanity.com/paper/2409.10337/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Sep 2024.

## Built on by (most cited first, 1 of 1)

- [Convolutional Neural Networks and Mixture of Experts for Intrusion Detection in 5G Networks and beyond](https://mlsanity.com/paper/2412.03483/) (2024)

## Abstract (arXiv)

The advent of 6G networks promises unprecedented advancements in wireless communication, offering wider bandwidth and lower latency compared to its predecessors. This article explores the evolving infrastructure of 6G networks, emphasizing the transition towards a more disaggregated structure and the integration of artificial intelligence (AI) technologies. Furthermore, it explores the security, trust and privacy challenges and attacks in 6G networks, particularly those related to the use of AI. It presents a classification of network attacks stemming from its AI-centric architecture and explores technologies designed to detect or mitigate these emerging threats. The paper concludes by examining the implications and risks linked to the utilization of AI in ensuring a robust network.