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9783668943407: Detection of Primary User Emulation Attack in Cognitive Radio Networks based on TDOA using Novel Bat Algorithm
  • EditorialGRIN Verlag
  • Año de publicación2019
  • ISBN 10 3668943400
  • ISBN 13 9783668943407
  • EncuadernaciónTapa blanda
  • IdiomaInglés
  • Número de edición1
  • Número de páginas92

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9786139459711: Detection Of Primary User Emulation Attack in Cognitive Radio Networks

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ISBN 10:  6139459710 ISBN 13:  9786139459711
Editorial: LAP LAMBERT Academic Publishing, 2019
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Rehman, Aasia
Publicado por Grin Verlag, 2019
ISBN 10: 3668943400 ISBN 13: 9783668943407
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Librería: California Books, Miami, FL, Estados Unidos de America

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Condición: New. Nº de ref. del artículo: I-9783668943407

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Aasia Rehman
Publicado por GRIN Verlag Mai 2019, 2019
ISBN 10: 3668943400 ISBN 13: 9783668943407
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Master's Thesis from the year 2017 in the subject Computer Science - General, grade: 8.63, , course: M. Tech - Cognitive Radio Networks, language: English, abstract: Cognitive Radio Network (CRN) Technology makes the efficient utilization of scarce spectrum resources by allowing the unlicensed users to opportunistically use the licensed spectrum bands. Cognitive Radio Technology has gained a lot of attention from the researchers over the years however insufficient research has been done related to its security. Cognitive Radio Network due to its flexible and open nature is vulnerable to a number of security attacks. In this thesis 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). A number of cooperative secondary users are used for detecting the PUEA by comparing its estimated position with the known position of incumbent. The main goal of Novel Bat Algorithm (NBA) is to minimize two fitness functions namely non-linear least square (NLS) and the maximum likelihood (ML) in order to optimize the error in estimation.After evaluation, simulation results clearly demonstrates that NBA results in reduced estimation error as compared to Taylor Series Estimation (TSE) and Particle Swarm Optimization (PSO) and it also needs smaller number of secondary users for cooperation. Also maximum likelihood function performs better than non-linear least square function. 92 pp. Englisch. Nº de ref. del artículo: 9783668943407

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Aasia Rehman
Publicado por GRIN Verlag, 2019
ISBN 10: 3668943400 ISBN 13: 9783668943407
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Librería: AHA-BUCH GmbH, Einbeck, Alemania

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Master's Thesis from the year 2017 in the subject Computer Science - General, grade: 8.63, , course: M. Tech - Cognitive Radio Networks, language: English, abstract: Cognitive Radio Network (CRN) Technology makes the efficient utilization of scarce spectrum resources by allowing the unlicensed users to opportunistically use the licensed spectrum bands. Cognitive Radio Technology has gained a lot of attention from the researchers over the years however insufficient research has been done related to its security. Cognitive Radio Network due to its flexible and open nature is vulnerable to a number of security attacks. In this thesis 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). A number of cooperative secondary users are used for detecting the PUEA by comparing its estimated position with the known position of incumbent. The main goal of Novel Bat Algorithm (NBA) is to minimize two fitness functions namely non-linear least square (NLS) and the maximum likelihood (ML) in order to optimize the error in estimation.After evaluation, simulation results clearly demonstrates that NBA results in reduced estimation error as compared to Taylor Series Estimation (TSE) and Particle Swarm Optimization (PSO) and it also needs smaller number of secondary users for cooperation. Also maximum likelihood function performs better than non-linear least square function. Nº de ref. del artículo: 9783668943407

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Aasia Rehman
Publicado por GRIN Verlag, 2019
ISBN 10: 3668943400 ISBN 13: 9783668943407
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Librería: preigu, Osnabrück, Alemania

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Taschenbuch. Condición: Neu. Detection of Primary User Emulation Attack in Cognitive Radio Networks based on TDOA using Novel Bat Algorithm | Aasia Rehman | Taschenbuch | 92 S. | Englisch | 2019 | GRIN Verlag | EAN 9783668943407 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Nº de ref. del artículo: 116775446

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