面向6G NTN的边缘AI赋能物理层安全：潜在威胁与未来机遇
Edge AI Empowered Physical Layer Security for 6G NTN: Potential Threats and Future Opportunities
AI总结：
本文概述了6G NTN中物理层面临的潜在风险，并回顾了边缘AI增强物理层安全的前沿设计策略，为构建下一代可信6G电信网络奠定基础。
摘要：
由于人工智能（AI）服务器在经济利润方面具有巨大潜力，网络安全领域有可能成为全球范围内企业和政府竞争的重要舞台。AI技术进步有望受益的领域之一便是网络安全。为此，本文概述了在6G非地面网络（NTN）背景下物理层可能面临的潜在风险。为了展示前沿AI技术在增强物理层安全方面的有效性，本研究回顾了将边缘AI集成到6G NTN领域中最具预见性的设计策略。本文的研究结果提供了一些见解，并为未来旨在增强下一代可信6G电信网络中边缘服务器/设备物理层安全的研究奠定了基础。
英文摘要：
Due to the enormous potential for economic profit offered by artificial intelligence (AI) servers, the field of cybersecurity has the potential to emerge as a prominent arena for competition among corporations and governments on a global scale. One of the prospective applications that stands to gain from the utilization of AI technology is the advancement in the field of cybersecurity. To this end, this paper provides an overview of the possible risks that the physical layer may encounter in the context of 6G Non-Terrestrial Networks (NTN). With the objective of showcasing the effectiveness of cutting-edge AI technologies in bolstering physical layer security, this study reviews the most foreseeable design strategies associated with the integration of edge AI in the realm of 6G NTN. The findings of this paper provide some insights and serve as a foundation for future investigations aimed at enhancing the physical layer security of edge servers/devices in the next generation of trustworthy 6G telecommunication networks.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
