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Aggiungi al carrelloTaschenbuch. Condizione: 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.
Da: Basi6 International, Irving, TX, U.S.A.
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Aggiungi al carrelloCondizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Aggiungi al carrelloTaschenbuch. Condizione: 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.
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Editore: Taylor & Francis Ltd, London, 2024
ISBN 10: 1032530189 ISBN 13: 9781032530185
Lingua: Inglese
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. Artificial intelligence (AI) and its applications have risen to prominence as one of the most active study areas in recent years. In recent years, a rising number of AI applications have been applied in a variety of areas. Agriculture, transportation, medicine, and health are all being transformed by AI technology. The Internet of Things (IoT) market is thriving, having a significant impact on a wide variety of industries and applications, including e-health care, smart cities, smart transportation, and industrial engineering. Recent breakthroughs in artificial intelligence and machine learning techniques have reshaped various aspects of artificial vision, considerably improving the state of the art for artificial vision systems across a broad range of high-level tasks. As a result, several innovations and studies are being conducted to improve the performance and productivity of IoT devices across multiple industries using machine learning and artificial intelligence. Security is a primary consideration when analyzing the next generation communication network due to the rapid advancement of technology. Additionally, data analytics, deep intelligence, deep learning, cloud computing, and intelligent solutions are being employed in medical, agricultural, industrial, and health care systems that are based on the Internet of Things. This book will look at cutting-edge Network Attacks and Security solutions that employ intelligent data processing and Machine Learning (ML) methods.This book:Covers emerging technologies of network attacks and management aspectsPresents artificial intelligence techniques for networks and resource optimization, and toward network automation, and securityShowcases recent industrial and technological aspects of next-generation networksIllustrates artificial intelligence techniques to mitigate cyber-attacks, authentication, and authorization challengesExplains smart, and real-time monitoring services, multimedia, cloud computing, and information processing methodologies in 5G networksIt is primarily for senior undergraduates, graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology This book will look at cutting-edge Network Attacks and Security solutions that employ intelligent data processing and Machine Learning (ML) methods. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Da: Ria Christie Collections, Uxbridge, Regno Unito
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Aggiungi al carrelloHardcover. Condizione: Brand New. 240 pages. 9.19x6.13x9.21 inches. In Stock.
Editore: Taylor & Francis Ltd, London, 2024
ISBN 10: 1032530189 ISBN 13: 9781032530185
Lingua: Inglese
Da: CitiRetail, Stevenage, Regno Unito
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. Artificial intelligence (AI) and its applications have risen to prominence as one of the most active study areas in recent years. In recent years, a rising number of AI applications have been applied in a variety of areas. Agriculture, transportation, medicine, and health are all being transformed by AI technology. The Internet of Things (IoT) market is thriving, having a significant impact on a wide variety of industries and applications, including e-health care, smart cities, smart transportation, and industrial engineering. Recent breakthroughs in artificial intelligence and machine learning techniques have reshaped various aspects of artificial vision, considerably improving the state of the art for artificial vision systems across a broad range of high-level tasks. As a result, several innovations and studies are being conducted to improve the performance and productivity of IoT devices across multiple industries using machine learning and artificial intelligence. Security is a primary consideration when analyzing the next generation communication network due to the rapid advancement of technology. Additionally, data analytics, deep intelligence, deep learning, cloud computing, and intelligent solutions are being employed in medical, agricultural, industrial, and health care systems that are based on the Internet of Things. This book will look at cutting-edge Network Attacks and Security solutions that employ intelligent data processing and Machine Learning (ML) methods.This book:Covers emerging technologies of network attacks and management aspectsPresents artificial intelligence techniques for networks and resource optimization, and toward network automation, and securityShowcases recent industrial and technological aspects of next-generation networksIllustrates artificial intelligence techniques to mitigate cyber-attacks, authentication, and authorization challengesExplains smart, and real-time monitoring services, multimedia, cloud computing, and information processing methodologies in 5G networksIt is primarily for senior undergraduates, graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology This book will look at cutting-edge Network Attacks and Security solutions that employ intelligent data processing and Machine Learning (ML) methods. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Editore: Taylor & Francis Ltd, London, 2024
ISBN 10: 1032530189 ISBN 13: 9781032530185
Lingua: Inglese
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. Artificial intelligence (AI) and its applications have risen to prominence as one of the most active study areas in recent years. In recent years, a rising number of AI applications have been applied in a variety of areas. Agriculture, transportation, medicine, and health are all being transformed by AI technology. The Internet of Things (IoT) market is thriving, having a significant impact on a wide variety of industries and applications, including e-health care, smart cities, smart transportation, and industrial engineering. Recent breakthroughs in artificial intelligence and machine learning techniques have reshaped various aspects of artificial vision, considerably improving the state of the art for artificial vision systems across a broad range of high-level tasks. As a result, several innovations and studies are being conducted to improve the performance and productivity of IoT devices across multiple industries using machine learning and artificial intelligence. Security is a primary consideration when analyzing the next generation communication network due to the rapid advancement of technology. Additionally, data analytics, deep intelligence, deep learning, cloud computing, and intelligent solutions are being employed in medical, agricultural, industrial, and health care systems that are based on the Internet of Things. This book will look at cutting-edge Network Attacks and Security solutions that employ intelligent data processing and Machine Learning (ML) methods.This book:Covers emerging technologies of network attacks and management aspectsPresents artificial intelligence techniques for networks and resource optimization, and toward network automation, and securityShowcases recent industrial and technological aspects of next-generation networksIllustrates artificial intelligence techniques to mitigate cyber-attacks, authentication, and authorization challengesExplains smart, and real-time monitoring services, multimedia, cloud computing, and information processing methodologies in 5G networksIt is primarily for senior undergraduates, graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology This book will look at cutting-edge Network Attacks and Security solutions that employ intelligent data processing and Machine Learning (ML) methods. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Editore: LAP LAMBERT Academic Publishing Apr 2018, 2018
ISBN 10: 613982723X ISBN 13: 9786139827237
Lingua: Inglese
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 35,90
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Intrusion Detection Systems uses multiple methods to detect and prevent network attacks. A good IDS should be designed to reduce false positives and to ensure that only actual malicious traffic is detected and stopped .This study focuses on detecting the presence of malicious nodes that selectively or randomly drop packets intended for other destination nodes in Mobile Ad-hoc Networks(MANETs) ,it further classifies each packet drop attack, according to its attack type by observing and analyzing how each packet drop attack affect the network characteristics. Network security monitoring is based on the principle that prevention eventually fails. In the current threat landscape, no matter how much you try, motivated attackers will eventually find their way into your network. At that point, your ability to detect and respond to that intrusion can be the difference between a small incident and a major disaster. This study follows a three-stage cycle: i. data collection ii. data analysis iii. detection and classification. This syudy motivates the intelligent use of artificial neural networks that makes use of local data collected at each node in detecting malicious activities. 84 pp. Englisch.
Editore: LAP LAMBERT Academic Publishing, 2018
ISBN 10: 613982723X ISBN 13: 9786139827237
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 37,20
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Intrusion Detection Systems uses multiple methods to detect and prevent network attacks. A good IDS should be designed to reduce false positives and to ensure that only actual malicious traffic is detected and stopped .This study focuses on detecting the presence of malicious nodes that selectively or randomly drop packets intended for other destination nodes in Mobile Ad-hoc Networks(MANETs) ,it further classifies each packet drop attack, according to its attack type by observing and analyzing how each packet drop attack affect the network characteristics. Network security monitoring is based on the principle that prevention eventually fails. In the current threat landscape, no matter how much you try, motivated attackers will eventually find their way into your network. At that point, your ability to detect and respond to that intrusion can be the difference between a small incident and a major disaster. This study follows a three-stage cycle: i. data collection ii. data analysis iii. detection and classification. This syudy motivates the intelligent use of artificial neural networks that makes use of local data collected at each node in detecting malicious activities.
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 47,95
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Aggiungi al carrelloTaschenbuch. Condizione: 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.
Editore: LAP LAMBERT Academic Publishing, 2018
ISBN 10: 613982723X ISBN 13: 9786139827237
Lingua: Inglese
Da: moluna, Greven, Germania
EUR 31,27
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Mapanga InnocentInnocent Mapanga was born in Zimbabwe. He received his B.Sc. Honors degree in Computer Science from Bindura University of Science Education, Zimbabwe, in 2008 and an MTech in Computer Science & Engineering from Delhi .
Da: PBShop.store US, Wood Dale, IL, U.S.A.
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Aggiungi al carrelloHRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: Revaluation Books, Exeter, Regno Unito
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Aggiungi al carrelloHardcover. Condizione: Brand New. 240 pages. 9.19x6.13x9.21 inches. In Stock. This item is printed on demand.
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 147,50
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Aggiungi al carrelloHRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: moluna, Greven, Germania
EUR 113,55
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr. Sagar Dhanraj PandeAssistant Professor, Department of Computer Science and Engineering, School of Engineering and Technology, Pimpri Chinchwad University (PCU), Pune, Maharashtra, India.Dr. Sagar Dhanraj Pande has exper.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 169,51
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Aggiungi al carrelloBuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book will look at cutting-edge Network Attacks and Security solutions that employ intelligent data processing and Machine Learning (ML) methods.