SECURITY AND INTELLIGENCE MEASURE IN ONLINE MACHINE LEARNING-BASED DYNAMIC SPECTRUM SHARING NETWORKS

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dc.creatorMonireh Dabaghchian
dc.date.accessioned2022-01-25T19:05:46Z
dc.date.available2022-01-25T19:05:46Z
dc.date.issued2019
dc.description.abstractCognitive radio (CR) is considered as a key enabling technology for dynamic spectrum access to improve spectrum eciency. This dissertation studies the two aspects of spectrum sharing networks: Security and intelligence capabilities. In the rst part, we consider a a primary user emulation (PUE) attacker that can send falsied primary user signals and prevent the secondary user from utilizing the available channel. The best attacking strategies that an attacker can apply have not been well studied. In this thesis, for the rst time, we study optimal
dc.identifier.urihttps://hdl.handle.net/1920/12275
dc.titleSECURITY AND INTELLIGENCE MEASURE IN ONLINE MACHINE LEARNING-BASED DYNAMIC SPECTRUM SHARING NETWORKS
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorGeorge Mason University
thesis.degree.levelPh.D.

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