mlsanityData to 14 Oct 2026

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

arXiv 2208.01221 ↗First posted 2 Aug 2022cs.NI cs.AI cs.LGcited by 2

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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.

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.

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2 of 19 references.

References · 2

  1. 2021Multi-Perspective Trust Management Framework for Crowdsourced IoT Servicescited by 3
  2. 2022A Secure Clustering Protocol with Fuzzy Trust Evaluation and Outlier Detection for Industrial Wireless Sensor Networkscited by 2

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2 papers.