Isbn: 9786204748757 - effective solutions for cross layer attacks in cognitive radio network: detection of malicious users during cross layer attacks (8 resultados)

Condición: New.

Taschenbuch. Condición: Neu. Effective Solutions for Cross Layer Attacks in Cognitive Radio Network | Detection of Malicious Users during Cross Layer Attacks | Ganesh Davanam (u. a.) | Taschenbuch | Englisch | 2022 | LAP LAMBERT Academic Publishing | EAN 9786204748757 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

Condición: New. Print on Demand.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Cognitive Radio Networks (CRNs) have come out as an encouraging next-generation network technology that addresses the issues related to dynamic Spectrum Access and enhanced utilization of spectrum in a significant manner. Specifically Trust, Reputation Management models and Cross layer defense mechanism are more and more regarded for CRNs to secure them against the attacks posed by the secondary users. In this Work, a method called, Mean Bid Trust & Multiple Nash Reputation (MBT-MNR) and Optimized Levensthein Cross layer Defense framework methods are proposed to secure the CRN by detecting the attackers at two different layers, Physical and Data link layers. Mean Bid Cross Layer Trust Evaluation model is applied to measure the trustworthiness of secondary user by third party. Followed by which, the classification of malicious and normal user is made by applying the Multiple Nash Game Theory model. Optimized Levesthein Nearest Centroid Framework (OS-LNCC) is proposed to mitigate Cross Layer attacks in CRN's. The performance of both the methods is evaluated by various parameters such as energy consumption, detection time, Sensing Delay, Throughput and detection accuracy. 96 pp. Englisch.…

Condición: New. PRINT ON DEMAND.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Cognitive Radio Networks (CRNs) have come out as an encouraging next-generation network technology that addresses the issues related to dynamic Spectrum Access and enhanced utilization of spectrum in a significant manner. Specifically Trust, Reputation Mana.…

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Cognitive Radio Networks (CRNs) have come out as an encouraging next-generation network technology that addresses the issues related to dynamic Spectrum Access and enhanced utilization of spectrum in a significant manner. Specifically Trust, Reputation Management models and Cross layer defense mechanism are more and more regarded for CRNs to secure them against the attacks posed by the secondary users. In this Work, a method called, Mean Bid Trust & Multiple Nash Reputation (MBT-MNR) and Optimized Levensthein Cross layer Defense framework methods are proposed to secure the CRN by detecting the attackers at two different layers, Physical and Data link layers. Mean Bid Cross Layer Trust Evaluation model is applied to measure the trustworthiness of secondary user by third party. Followed by which, the classification of malicious and normal user is made by applying the Multiple Nash Game Theory model. Optimized Levesthein Nearest Centroid Framework (OS-LNCC) is proposed to mitigate Cross Layer attacks in CRN's. The performance of both the methods is evaluated by various parameters such as energy consumption, detection time, Sensing Delay, Throughput and detection accuracy.…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Cognitive Radio Networks (CRNs) have come out as an encouraging next-generation network technology that addresses the issues related to dynamic Spectrum Access and enhanced utilization of spectrum in a significant manner. Specifically Trust, Reputation Management models and Cross layer defense mechanism are more and more regarded for CRNs to secure them against the attacks posed by the secondary users. In this Work, a method called, Mean Bid Trust & Multiple Nash Reputation (MBT-MNR) and Optimized Levensthein Cross layer Defense framework methods are proposed to secure the CRN by detecting the attackers at two different layers, Physical and Data link layers. Mean Bid Cross Layer Trust Evaluation model is applied to measure the trustworthiness of secondary user by third party. Followed by which, the classification of malicious and normal user is made by applying the Multiple Nash Game Theory model. Optimized Levesthein Nearest Centroid Framework (OS-LNCC) is proposed to mitigate Cross Layer attacks in CRN's. The performance of both the methods is evaluated by various parameters such as energy consumption, detection time, Sensing Delay, Throughput and detection accuracy.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 96 pp. Englisch.…