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When Machine Learning Meets Spectrum Sharing Security: Methodologies and Challenges. (arXiv:2201.04677v1 [cs.CR])
Jan. 14, 2022, 2:10 a.m. | Qun Wang, Haijian Sun, Rose Qingyang Hu, Arupjyoti Bhuyan
cs.LG updates on arXiv.org arxiv.org
The exponential growth of internet connected systems has generated numerous
challenges, such as spectrum shortage issues, which require efficient spectrum
sharing (SS) solutions. Complicated and dynamic SS systems can be exposed to
different potential security and privacy issues, requiring protection
mechanisms to be adaptive, reliable, and scalable. Machine learning (ML) based
methods have frequently been proposed to address those issues. In this article,
we provide a comprehensive survey of the recent development of ML based SS
methods, the most critical …
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