# Generative AI for Cyber Threat-Hunting in 6G-enabled IoT Networks

arXiv: https://arxiv.org/abs/2303.11751 · HTML: https://mlsanity.com/paper/2303.11751/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Mar 2023.

## Built on by (most cited first, 9 of 9)

- [Revolutionizing Cyber Threat Detection with Large Language Models: A privacy-preserving BERT-based Lightweight Model for IoT/IIoT Devices](https://mlsanity.com/paper/2306.14263/) (2023)
- [From Generative AI to Generative Internet of Things: Fundamentals, Framework, and Outlooks](https://mlsanity.com/paper/2310.18382/) (2023)
- [Applications of Generative AI (GAI) for Mobile and Wireless Networking: A Survey](https://mlsanity.com/paper/2405.20024/) (2024)
- [Generative Artificial Intelligence for Internet of Things Computing: A Systematic Survey](https://mlsanity.com/paper/2504.07635/) (2025)
- [Security Risks Concerns of Generative AI in the IoT](https://mlsanity.com/paper/2404.00139/) (2024)
- [A Survey on the Application of Generative Adversarial Networks in Cybersecurity: Prospective, Direction and Open Research Scopes](https://mlsanity.com/paper/2407.08839/) (2024)
- [A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection](https://mlsanity.com/paper/2412.19830/) (2024)
- [A Survey on AI for 6G: Challenges and Opportunities](https://mlsanity.com/paper/2604.02370/) (2026)
- [Generative AI-enabled Blockchain Networks: Fundamentals, Applications, and Case Study](https://mlsanity.com/paper/2401.15625/) (2024)

## Abstract (arXiv)

The next generation of cellular technology, 6G, is being developed to enable a wide range of new applications and services for the Internet of Things (IoT). One of 6G's main advantages for IoT applications is its ability to support much higher data rates and bandwidth as well as to support ultra-low latency. However, with this increased connectivity will come to an increased risk of cyber threats, as attackers will be able to exploit the large network of connected devices. Generative Artificial Intelligence (AI) can be used to detect and prevent cyber attacks by continuously learning and adapting to new threats and vulnerabilities. In this paper, we discuss the use of generative AI for cyber threat-hunting (CTH) in 6G-enabled IoT networks. Then, we propose a new generative adversarial network (GAN) and Transformer-based model for CTH in 6G-enabled IoT Networks. The experimental analysis results with a new cyber security dataset demonstrate that the Transformer-based security model for CTH can detect IoT attacks with a high overall accuracy of 95%. We examine the challenges and opportunities and conclude by highlighting the potential of generative AI in enhancing the security of 6G-enabled IoT networks and call for further research to be conducted in this area.