Detection Of Primary User Emulation Attack in Cognitive Radio Networks

Aasia Rehman

ISBN 10: 6139459710 / ISBN 13: 9786139459711

Edité par LAP LAMBERT Academic Publishing, 2019

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nach der Bestellung gedruckt Neuware - Printed after ordering - In this work we recognize di erent types of attacks at di erent layers of protocol stack. This thesis is mainly concerned with one of the physical layer attack called Primary User Emulation Attack and its detection. PUE Attack adversely a ects the CRN performance and can also sometimes lead to Denial of Service to CR networks. In Primary User Emulation Attack the attacker imitates the signal characteristics of the Primary User. This thesis first provides introduction to CRN, its architecture and sensing techniques and also discusses various attacks and their counter measures. Then it mainly focuses on PUE attack and examines its mitigation techniques. This thesis solves the problem of PUE attack by localization technique based on TDOA measurements with reduced error in location estimation using a Novel Bat Algorithm (NBA). N° de réf. du vendeur 9786139459711

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Titre : Detection Of Primary User Emulation Attack ...

Éditeur : LAP LAMBERT Academic Publishing

Date d'édition : 2019

Reliure : Taschenbuch

Etat : Neu

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Synopsis :

In this work we recognize different types of attacks at different layers of protocol stack. This thesis is mainly concerned with one of the physical layer attack called Primary User Emulation Attack and its detection. PUE Attack adversely affects the CRN performance and can also sometimes lead to Denial of Service to CR networks. In Primary User Emulation Attack the attacker imitates the signal characteristics of the Primary User. This thesis first provides introduction to CRN, its architecture and sensing techniques and also discusses various attacks and their counter measures. Then it mainly focuses on PUE attack and examines its mitigation techniques. This thesis solves the problem of PUE attack by localization technique based on TDOA measurements with reduced error in location estimation using a Novel Bat Algorithm (NBA).