Date: January 29th, 2021
Time: 10-11AM ET

Title: AI and Machine Leaning in Spectrum Sharing Security

Abstract: Dynamic spectrum sharing has been widely considered a key enabler of supporting future wireless networks for massive connectivity and pervasive communications. The complexity and dynamics of the spectrum sharing systems are being exposed to various new attacks, which require novel security and protecting mechanisms that are adaptive, reliable, and scalable. Artificial intelligence and Machine learning based methods have been widely explored to address these issues. In this talk, we will present the recent research advancements in AI/ML based spectrum sharing as well as the corresponding security mechanisms. In particular, we will focus on the state-of-art methodologies for improving the performance of the spectrum sharing communication systems by using AI/ML in different sharing paradigms such as cognitive radio networks, Licensed shared access/spectrum access systems, LTE-U/LAA networks, and ambient backscatter networks. How AI and ML are used to tackle spectrum sharing specific security issues such as primary user emulation attacks, spectrum sensing data falsification attacks, jamming/eavesdrop attacks, privacy issues, as well as how AL/ML can be possibly exploited to launch adversarial attacks in the spectrum sharing systems will be further elaborated. We expect that this talk will highlight the challenges as well as research opportunities in exploring AI and ML techniques to support the ever increasingly important yet complicated spectrum sharing as well as the related security mechanisms.


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