# Generative Adversarial Learning for Intelligent Trust Management in 6G Wireless Networks

arXiv: https://arxiv.org/abs/2208.01221 · HTML: https://mlsanity.com/paper/2208.01221/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 19 references that are in the map.
- First posted on arXiv 2 Aug 2022.

## Builds on (most cited first, 2 of 2)

- [Multi-Perspective Trust Management Framework for Crowdsourced IoT Services](https://mlsanity.com/paper/2101.04244/) (2021)
- [A Secure Clustering Protocol with Fuzzy Trust Evaluation and Outlier Detection for Industrial Wireless Sensor Networks](https://mlsanity.com/paper/2207.09936/) (2022)

## Built on by (most cited first, 2 of 2)

- [Applications of Generative AI (GAI) for Mobile and Wireless Networking: A Survey](https://mlsanity.com/paper/2405.20024/) (2024)
- [Embracing the Generative AI Revolution: Advancing Tertiary Education in Cybersecurity with GPT](https://mlsanity.com/paper/2403.11402/) (2024)

## Abstract (arXiv)

Emerging six generation (6G) is the integration of heterogeneous wireless networks, which can seamlessly support anywhere and anytime networking. But high Quality-of-Trust should be offered by 6G to meet mobile user expectations. Artificial intelligence (AI) is considered as one of the most important components in 6G. Then AI-based trust management is a promising paradigm to provide trusted and reliable services. In this article, a generative adversarial learning-enabled trust management method is presented for 6G wireless networks. Some typical AI-based trust management schemes are first reviewed, and then a potential heterogeneous and intelligent 6G architecture is introduced. Next, the integration of AI and trust management is developed to optimize the intelligence and security. Finally, the presented AI-based trust management method is applied to secure clustering to achieve reliable and real-time communications. Simulation results have demonstrated its excellent performance in guaranteeing network security and service quality.